Watch Me Complete My Sem Syllabus 10 days before exam #day6

Added: 2026-05-15

[00:00:24]Okay. So this is uh day six of 10 days of completing my SAM syllabus before 10 days of exam and I have consistently followed four days and the fifth day was um no no situation because Wi-Fi wasn't there and today day six we are continuing it Sanjana hi so we are now going to start our live session where we are going to complete our sim syllabus and right now I'm going to study my computer vision and image processing subject. Uh it's also given by college question bank. Uh today is the day they have given us the question bank for computer vision and image processing. So I'm going to study the question bank.

[00:01:10]Yeah. So we'll have a Q&A session for first 10 minutes and then after 10 minutes we'll lock in for 40 minutes we'll study. So let me know what you guys are studying right now. Sanja, what do you want to study?

[00:01:31]>> Mr. Anonymous. Hi. What do you want to study for this session?

[00:01:41]M.

[00:01:49]>> Which semester are you from?

[00:02:06]second semester. Okay. So, you are from first year. Are you from Sandep University?

[00:02:14]So, yesterday I didn't read anything.

[00:02:17]Today is very crucial for me.

[00:02:22]Lea, hi Mr. Anonymous.

[00:02:27]What are you? Don't you want to study right now?

[00:02:34][snorts] >> It's really very hard to keep it up during exams.

[00:02:53]So drop down what you want to study for this session. Which subject are you studying or which topic you want to study?

[00:03:02]Or if you have any questions also you're welcome.

[00:03:24]So till when do you want to study?

[00:03:27]Should we do two sessions today or only one session?

[00:03:50]only one session. So you don't want to study long today. Okay, we'll see. As what many people say, we'll do that one.

[00:04:02]When are your semester exams?

[00:04:10]>> [snorts] >> Uh, Chandra Manikanta, I actually committed to the 10 days challenge, but I'm not really making progress with it.

[00:04:23]I just managed to do the basics, but I haven't even done two chapters yet. I only have three days left. So, we are going to work hard these three days.

[00:04:36]All the best Sanja for your exams mostly I'm following question banks for the subjects that were given CVIP and SCPM no we didn't get SCPM one d CVIP sa algorithms and CVIP. I'm following question banks.

[00:05:09]I don't know what to do with the remaining two subjects and so if you have any questions drop them down or we'll start the 40 minute locking session.

[00:05:50]When do you like to study more? Morning, early morning or night or evening?

[00:06:00]>> Should we do an early morning session tomorrow or morning, afternoon, evening?

[00:06:25]Late night. I guess that is only working late night. I will do late night sessions.

[00:06:37]Okay, then we'll start our 40 minute login session and we'll study for 40 minutes. Try it out. Open your books, study with me. Go grab your syllabus, books and everything. Sit as I sit here, study with me and doubts or doubts or suggestions in the comments or live chat.

[00:07:35]So if there are any Wi-Fi issues I assume and now I'm going to start my two marks questions right now. Do you want to study right now and at the end we'll discuss again whether you completed it?

[00:08:15]Welcome.

[00:08:35]Okay. So guys 2 3 minutes it will automatically resume. Sorry for the disturbance notify from my Instagram channel. Follow me there opportunities. I will soon make videos on them.

[00:08:57]So now we'll start our studying. Sorry I kept saying that again and again. I'm starting with my two marks questions.

[00:09:04]Drop down what you want to study.

[00:09:07]Hi Sai Chan, what do you want to study for this session?

[00:09:38]Tomorrow 16 days.

[00:10:06]I'm going to get this List two characteristics of perspective projection used in camera models.

[00:10:55]List two characteristics of perspective projection used in camera models for two marks.

[00:11:15]in camera models.

[00:11:21]Perspective projection mimics >> Perspective projection mimics how the human eye how the human eye and real world cameras perceive 3D objects in a 2D plane.

[00:11:46]Cameras cursive 3D objects on a 2D plane.

[00:12:01]Two fundamental characteristics include vanishing points.

[00:12:21]Parallel lines in 3D space are not parallel.

[00:12:25]parallel lines in 3D space that are not parallel to the image plane appear to converge at a single point appear to converge at a single point.

[00:12:54]the vanishing point in the 2D image.

[00:13:07]Size dimmonition.

[00:13:16]The size of an object's projection is inversely the size of an object's projection is inversely proportional to its distance from the camera.

[00:13:33]Is inversely proportional to the distance from the camera.

[00:13:52]State the purpose of object recognition.

[00:13:57]State the purpose of object recognition in computer vision applications.

[00:14:10]in computer vision applications.

[00:14:20]State the purpose of object recognition in computer vision applications for two marks.

[00:14:33]>> Uh I'm in my third year saran which year are you in?

[00:14:46]The primary purpose of object recognition in computer vision is to enable a system.

[00:15:05]Oh, which university are you from?

[00:15:16]The primary purpose of object recognition in computer vision is to enable a system to both identify and locate.

[00:15:40]Trial D3P. Please don't be rude here to both identify and locate specific objects within an image or video.

[00:16:06]stream. So the primary purpose of an object recognition in computer vision is to enable a system to both identify and locate specific objects within an image or video stream.

[00:16:29]Assigning a label to an object.

[00:16:36]assigning a label to an object.

[00:16:41]Example, identifying that a group of pixels Identifying that a group of pixels represents a car or a person.

[00:17:03]Localization determining the exact position and boundaries. object. Determining the exact position and boundaries of that object within the visual field.

[00:17:36]within the visual field. Often represented by bounding box often represented by a bounding box.

[00:17:57]I am Ohara Institute [clears throat] of Technology.

[00:18:03]Is it true? I'm set.

[00:18:13]We only have 27 minutes left to go.

[00:18:18]Keep studying.

[00:18:25]Define lens distortion and image processing.

[00:18:31]Define lens distortion and image crossing.

[00:18:43]Define lens distortion and image processing for two months. Reduce the size.

[00:18:54]>> Did you get into that college through MSET?

[00:19:08]Lens distortion is an optical abrasion where a camera lens is an optical abrasion where a camera lens fails to project straight lines.

[00:19:32]fails to project straight lines in the physical world.

[00:19:40]in the physical world as straight lines in an image.

[00:19:50]>> as straight lines in an image.

[00:20:05]Okay. Hi Sharon. So which subject which subject are you studying right now? When do you have your semester exams?

[00:20:19]Lens distortion is an optical abrasion where a camera fails to project lines in the physical world as bright lines in an image.

[00:20:30]Okay.

[00:20:33]Image processing is the use of computer algorithms.

[00:20:44]Computer algorithms to perform operations. Image processing is use of computer algorithms to perform operations on a digital image.

[00:21:00]on a digital image to enhance its quality or extract useful information.

[00:21:27]Define the term feature detection in a computer vision.

[00:21:34]Define the term feature detection in computer vision.

[00:21:45]Even I am looking for internship opportunities. I actually I'm not selected for all the ones I did apply. I'm also searching for internships and I have joined many groups for that. I have applied for summer internships from IIT but unfortunately I didn't get get selected yet. So even I am looking for answers.

[00:22:13]Define the term feature detection in computer vision.

[00:22:52]It's okay. It's no problem. Just keep studying with me. Keep study as long as I study. Drop the subject you want to study in. And then at the last tell me whether you have completed your goal or not feature detection is the process feature detection is the process of identifying Just points or localized structures or localized structures in an image that contain significant information that contain significant informations for analysis. Feature detection is the process of identifying in points or localized structures uh in an image that contains significant information for analysis. The three key okay okay the key properties are features must be invariant unchanging to transformations like scaling rotation and illumination types common features include edges intensity gradients corners junction of edges and regions of uniform intensity thank you so much m1 and m2 kosome tips Okay. So usually first question you need to understand the pattern so that you should be able to do that do that at least minimum 10 to 15 questions you can understand how to write it in exam.

[00:25:17]You need to focus on internals interning marks and types of questions.

[00:25:34]Write it in your notebook.

[00:25:40]You need to change the questions and be able to do that by yourself for analysis.

[00:25:53]Key properties.

[00:25:57]We are halfway through the challenge.

[00:26:01]20 more minutes to peaches.

[00:26:08]must be invariant, unchanging to transformations like transformations like scaling, rotation and illumination.

[00:26:37]types.

[00:26:42]Common features include edges, intensity gradients, corners, junctions of edges and blocks.

[00:27:08]regions of uniform intensity CSC tomorrow exam 2 three days I don't know from 16th May List the applications of computer vision.

[00:27:45]N4.

[00:27:52]List the applications of computer vision. An NE4.

[00:28:02]Relax.

[00:28:16]I think autonomous vehicles.

[00:28:32]Robin creator high autonomous vehicles realtime detection of traffic signs, lanes and obstacles for navigation and obstacles for navigation.

[00:29:03]Okay, I'm from sep university medical imaging.

[00:29:18]Automated diagnosis of tumors or fractures from X-rays and Viper Gaming. May I know who is this?

[00:29:43]and exam please uh don't hope that I will write in already I'm about to get a backlog so Medical amazing.

[00:31:56]Am I clear now? Am I audible right now?

[00:32:11]Let me know if I'm audible.

[00:32:15]Okay.

[00:32:17]Biometric security.

[00:32:23]Facial recognition for identity.

[00:32:27]Spacial recognition for identity verification and surveillance.

[00:32:38]and surveillance goal to have more money and freedom to be independent.

[00:33:02]case I as you asked. My goal is to be independent, have freedom and earn as much money as I can.

[00:33:17]Industrial inspection automated quality control.

[00:33:27]Automated quality control.

[00:33:32]MIGO leni to detect defects in manufacturing lives.

[00:33:44]Manufacturing lights.

[00:33:56]Define the term image processing.

[00:34:02]Define the term.

[00:34:05]We have 11 more minutes left. So keep studying with me for this 11 minutes.

[00:34:10]After after that we'll have a 10 more minute Q&A session. So I'll answer each and every one of your questions.

[00:34:38]Define the term image processing.

[00:34:48]Define the term image processing.

[00:35:08]Don't reject your insecurities.

[00:35:21]Image processing is the use of computer algorithms.

[00:35:27]Image processing is the use of computer algorithms to perform mathematical operations.

[00:35:39]to perform mathematical operations on a digital image.

[00:35:51]On a digital image to enhance, it's okay. Just keep studying with me.

[00:36:03]Bring your books. Drop the topic you want to study and It's just okay live it. Let's not spread hate here. Let's study together. We are here to study together. If I really want to show up, I would have a video. I'm really trying to help me. I'm trying to get you motivated. So, keep studying with me. There are so many people who want to study just by seeing me study. I know that. So, study with me.

[00:36:38]enhance its quality or extract meaningful information.

[00:36:58]Define lens distortion in image processing.

[00:37:03]define lens distortion in image processing.

[00:37:14]>> Define the term image processing. Image processing is use of computer algorithms to perform mathematical operations on a digital image to enhance its quality or extract manipulation. Define define lens distortion in image crossing.

[00:37:43]Uh I'm studying CVIP subject computer vision and image processing for my sixth semester exam which is in which is on 23rd April. Last subject we have for this semester.

[00:37:58]Sai Chan and Ral DP thank you so much for your support. I will do as you lens distortion often referred to as geometric distortion is an optical addition.

[00:38:31]is an optical aberration where the linear mapping between the 3D scene and the 2D plane is physically wedged is physically wedged by the camera lens.

[00:39:04]by the camera lens. Lens distortion, often referred to as geometry distortion, is an optical aberration where the linear mapping between the 3D scene and the 2D plane is physically bad by the camera lens.

[00:39:20]It is characterized by two primary types.

[00:39:25]It is characterized comparatively average top it's better to try off campus than on campus.

[00:39:59]on campus.

[00:40:22]It's characterized by two primary types.

[00:40:28]Radial distortion which consigns of barrel and pin cushion tangential distortion.

[00:40:51]Okay. Then I I am questioning that to myself.

[00:41:00]Web development, a IML, computer vision are my main skills but they are not enough to get a full-fledged job or a high paying internship. in skills fullstack developmental. I have web development but I stuck in back in I know good IML machine learning algorithms I have good knowledge on them but I think I need to improve more skills.

[00:41:36]What is a syntactic recognition?

[00:41:44]What is a syntactic recognition?

[00:41:52]What is syntactic recognition?

[00:42:04]What is syntactic? Syntactic recognition.

[00:42:29]>> I want to search for internships too.

[00:42:32]If not internships, I have an internship training opportunity. I will join that one.

[00:42:47]Syntactic [snorts] or structural recognition is a pattern recognition is a pattern recognition method.

[00:43:17]that describes complex objects through their hierarchal structure.

[00:43:32]Hierarchal structure and the relationships between and the relationships between simpler components.

[00:43:51]Syntactic recognition is a pattern recognition method that describes complex objects. Is a pattern recognition method that describes complex objects through their hierarchal structure and the relationship between simpler components. Primitives. It decomposes a pattern into basic building blocks called primitives. Examples, lines, arcs or shapes. Grammar based. It uses formal grammars rules to define how these primitives must be connected or arranged to represent a specific object class.

[00:44:24]Primitives grammar based syntactic recognition is a pattern recognition method that describes complex objects through their hierarchal structure and the relationship between simpler components primitives. Grammar based primitives deco composes a pattern into basic building blocks called primitives lines after ships. It uses formal grammars rules to define how these primitives must be constructed or arranged to represent a specific object class [snorts] primitives.

[00:45:06]It decomposes a pattern into basic building blocks called into basic building blocks called primitives.

[00:45:30]Example, lines, arcs, or shapes, grammar based.

[00:45:46]It uses formal grammars, rules to define How this primitives must be arranged or connected or connected to represent a specific object.

[00:46:28]class.

[00:46:31]Uh Sai Chan, you need to learn skills first of all. If you are talking about this session, I okay you want to be fullstack developer.

[00:46:40]I suggest you learn skills from YouTube first and then try some paid opportunities or build projects by yourself. You can explore many projects.

[00:46:48]If you want to be fullstack developer, there are two things that is front end and back end. uh you need to learn HTML, CSS, JavaScript, ReactJS and then go to the back end NodeJS, EJS, uh ExpressJS you need to learn all APIs next all of them. Okay. So if you know do do that and then build some projects, build your resume, apply for internships. That is the process. If you want to be a fullstack web developer, you need to get internships and then after internships, you have two options whether you can convert that internship into a job or you can apply for other jobs as well.

[00:47:28]Okay. So he want to become a fullstack developer.

[00:47:34]But I'm telling if you want to be a fullstack developer the road map is to learn the basic skills first start this is the easiest full stack developer you need to learn front end and back end together it's called fullstack developer HTML CSS JavaScript reacts A4 depends on the language. JavaScript, NodeJS, Python, Django.

[00:48:29]Yes, SQL is comes under databases. So, you can learn from Google or you can try paid also. But it is better to go with freees in the YouTube.

[00:48:46]You need to build projects.

[00:48:52]It is waste.

[00:48:55]You need to create a GitHub account.

[00:49:04]So that is proof.

[00:49:12]You need to apply for internship.

[00:49:20]You will have two to three rounds.

[00:49:23]online assessment, technical interview, HR interview, you will get an internship opportunity.

[00:49:33]You can convert that into Okay.

[00:49:49]I don't know. It depends on your perspective.

[00:49:54]to change how they depends.

[00:50:06]I don't know if I should say that or not.

[00:50:14]I don't know. It depends on you. Come and check the university. If you love it, join. Don't depend on others.

[00:50:24][snorts] Red based on that and if you have better opportunities like others try exploring that before than this one.

[00:51:06]This should be your last plan.

[00:51:18]Should we continue the session another session 40 minutes till 12 or should we end this here? If you want to continue, drop a like.

[00:51:41]year ending I started learning web development and then I switched to a IML switch I explored the main skills I did internships If you want another session, just drop a like or else we'll wrap it up here.

[00:52:30][snorts] Okay. So, you're liking emoji.

[00:53:07]I mean chat emoji. I'll drop it. Okay.

[00:53:23]Easy.

[00:53:27]Leave study session.

[00:53:57]Like, like or just drop this emoji in the chat.

[00:54:46]Okay. So, we'll continue the session.

[00:54:50]We'll have 40 minutes of study session. But as for 911 asked, let's interact for 10 minutes and then we'll have the 40 minutes locking session and then again at the last we'll have a 10-minut Q&A session. Right now, Till 11:30 we'll have interactive session and then we'll lock in for 40 minutes. So drop it in the chat.

[00:55:28]Please be professional here. This is for only academical purposes.

[00:55:49]internships.

[00:55:51]You need to have at least a basic knowledge of course.

[00:55:57]You need to have at least 40 to 50% knowledge.

[00:56:10]zero knowledge.

[00:56:13]So you need to know at least 40 to 80% of the skills to get an internship.

[00:56:19]Non-coding type data analyst UIU You don't need to do much or if you can also go for these skills video editing, motion graphics, VFX coding, you will get a high paying jobs or internships. You can do it as a side hustle also.

[00:57:30]You will have groups. I kept saying this in every live grouper hunt group WhatsApp You can search for the specific groups, WhatsApp, you will get all the opportunities that are available out there.

[00:58:19]Yes. One Sari. Hi >> [snorts] >> Yeah, I don't know much about colleges.

[00:58:41]I don't think I'm not the right person to consult for college joining. If you have anything related to skills or coding or anything, I can help you with that. after joining college things but not I can't help you in which college to join. I'm really so sorry that I'm unable to help you.

[00:59:17]>> Yeah. Yes. You can give private college entrance exams like V with have some exams SRM with Vala.

[00:59:28]You can give exams for those.

[00:59:31]>> Yeah. Scale or NATO.

[00:59:38]May I know which year are you from?

[00:59:42]Porsch. Am I spelling it right?

[00:59:45]Pronouncing it right?

[00:59:48]Porch 911 programming.

[01:00:09]It is a nice idea. I'm still starting.

[01:00:12]Uh I'm trying which type of content works for me.

[01:00:16]I will definitely try to do programming.

[01:00:19]What do you think?

[01:00:25]I think telling about AI and ML would be better.

[01:00:36]Yeah, I thought so. I think doing a IML will be better because I'm also learning it. Okay. And I recently did a project on mata nindan.

[01:00:49]I wanted to do a video about it. It was related to computer vision.

[01:00:54]So I will put a video on it next week on my YouTube channel.

[01:01:01]Uh Rishi, let's be professional here.

[01:01:03]Let's not ask personal questions. If you have anything related to coding or academics or any suggestions related to college life, you can ask them. Or if you want to study with me, grab your books, sit here, study with me. Let's not take this personal. It's just academics or skills or something related to it.

[01:01:41]Perfect. Perfect.

[01:01:45]I mean, I'm still in my learning I'm trying to learn but I think I'm very good in machine learning algorithms. I can write code from scratch. So I will do videos on a IML, new tech or new AI tools and all that.

[01:02:29]No [laughter] day five would have joined in live.

[01:02:47]Let's consider day five.

[01:03:10]Okay, drop down what you want to study for this session. We'll start our second session right now. If you want to change your subject or topic or anything else skills, just drop down what you want to study for the second session.

[01:03:27]Or if you have any questions before starting the second session, go on drop it in the chat.

[01:03:38]I'm trying to learn skills and I really wanted to learn video editing but I think it's my mistake I'm not utilizing it and I'm trying for internships also based on the skills I already have.

[01:03:59]We'll see.

[01:04:08]mostly.

[01:04:14]Thank you children for your ad advice. I will try to learn skills.

[01:04:21]I will think about them.

[01:04:27]Okay, post 911, we'll start our second session. I'm going to continue my two marks questions from computer vision and image processing. So drop down what you want to study for this session. Porsche 911 or chair V2P what you're working on for this session. Gamer GP game T9 comment on what you want to study.

[01:05:02]I am thinking to join speaks course he's from YouTube.

[01:05:10]Thank you so much GPG for a day of consistency.

[01:05:14][snorts] Tren speaks. I really want to learn behavior editing course.

[01:05:25]That is why I want to learn.

[01:05:40]Okay. So, we'll start our next session.

[01:05:42]We'll study lock in for 40 minutes and then we'll have Q&A session at the last again. Till then we'll stay consistent.

[01:05:52]We will not talk. We will just study.

[01:06:14]comments from at least topics presenter computer vision and image processing subject two marks questions question bank uh if you have nothing to do I'll drop one explore this in live with render completely different C programming UI XM I think it better if you start coding depends on I think start with C very basic that is important I guess.

[01:07:48]So just explore what is that I name just recently complete this it is very good especially from this website wait but why we'll discuss about it at the last as you said go explore this being live with AMO I don't know I think you need to know basics I mean like you name it. Every top if you want high paying jobs. So, no need. You can learn UIUX also. But syntax is very important. You should not ignore [snorts] DSL top companies.

[01:10:23]It will be hard consistency data success and algorithms.

[01:10:45]stacks linked you need to know DSA starting sorting searching Erase Adids.

[01:11:34]Differentiate [snorts] between object detection and image classification. ation and image classification.

[01:12:13][laughter] Differentiate between object detection and image classification.

[01:12:31]Yes.

[01:13:11]>> [sighs and gasps] >> feature image classification.

[01:13:15]Object detection >> [snorts] >> Goal identifies what is in the image.

[01:13:42]10 minutes.

[01:13:48]So I had to answer. It is not good to study like that.

[01:14:02]Why? Let's study first then we'll discuss later what and where it is.

[01:14:25]Output [clears throat] single class label for the entire image.

[01:14:42]Class labels plus bounding boxes for multiple objects.

[01:15:03]differentiate between describe the pinhole camera.

[01:15:12]Describe the pinhole camera model.

[01:15:20]Pinhole camera model.

[01:15:24]Describe the pinhole camera model used in computer vision.

[01:15:37][snorts] Describe the pinhole camera model used in computer vision.

[01:15:58]The pinhole camera model is a mathematical description that maps 3D points.

[01:16:18]in the physical world onto a 2D image plane through a single point called the aperture or optical Yeah.

[01:17:15]Just one day.

[01:17:22]Identify two factors affecting phototric image formation.

[01:17:30]Identify two factors affecting.

[01:17:40]Identify two factors affecting phototric image formation.

[01:18:23]Photometric image. Age formation.

[01:18:29]Phototric formation describes describes how light intensity is captured as pixel values.

[01:18:56]illumination.

[01:19:00]The intensity, position, and color of the light source or sources striking the object.

[01:19:20]striking a object.

[01:19:22]Reflectance albido.

[01:19:29]The material property of the surface.

[01:19:36]The material property of the surface that determines how much light is that determines how much light is reflected toward the sensor.

[01:20:00]Example, diffuse versus specular.

[01:20:14]I'll be back in 2 minutes.

[01:20:18]Bye, sir.

[01:20:20]I'll be back in 2 minutes. I'll get my water.

[01:20:27]>> Stay with me. Don't go anywhere. They'll come into me.

[01:20:50]Fore! Foreign! Foreign!

[01:21:11]number.

[01:21:26]Okay.

[01:21:28]Fore about the table.

[01:22:39]Two properties of fine transformation in image geometry.

[01:22:46]In image geometry list two properties of fine transformation in image geometry for two marks.

[01:23:12]linearity and parallelism.

[01:23:18]Linearity and parallelism.

[01:23:23]Straight lines remain straight lines and parallel lines in the original image remain parallel lines after transformation.

[01:23:49]Parallel lines after transformation.

[01:23:59]Ratio of distances while length and angles may change.

[01:24:11]While lengths and angles may change, the ratio of lens along a straight line along a straight line segment is preserved.

[01:24:38]Hi Wayne E session.

[01:24:55]State the common applications of object detection.

[01:25:01]State the common applications of object detection.

[01:25:14]State the common applications of object detection for two marks.

[01:25:19][snorts] Autonomous navigation.

[01:25:34]Enabling selfdriving cars.

[01:25:40]Enabling self-driving cars.

[01:25:44]to detect and track pedestrians.

[01:25:49]To detect and track pedestrians, vehicles and traffic signs and traffic signs in real time.

[01:26:14]None of them. My brother, if he's watching this live, not Spider-Man, not Iron Man, my brother, radio surveillance, automated security systems, that identify unauthorized intrusion.

[01:26:57]Unauthorized intrusions, recognize spaces or detect suspicious Detect suspicious activities.

[01:27:23][snorts] Medical diagnosis.

[01:27:34]Locating specific lessons.

[01:27:39]Locating specific legends.

[01:27:43]tumors or anatomical structures within X-rays, MRIs and CT scans, industrial automation Identifying and counting items on assembly lines are detecting manufacturing defects in products.

[01:28:35]Are detecting manufacturing Defects and products.

[01:28:54]Define the concept of image formation.

[01:28:59]Define the concept of image form. Define the concept of image formation in computer vision systems.

[01:29:14]In computer vision systems, define the concept of image formation in computer vision systems for two marks.

[01:29:54]>> [snorts] >> In computer vision, Image formation is the process of mapping a 3D scene from the physical world.

[01:30:24]3D scene from the physical world onto a 2D distensor.

[01:30:59]Geometric component defines the special relationship between define the special relationship between 3D points and the 2D 3D projections and the 2D projections typically modeled by the pinhole by the pinhole.

[01:31:39]Camera model photometric component.

[01:31:47]Photometric component defines the pixel intensity defines the pixel intensity.

[01:32:04]Brightness or color based on factors like based on factors like illumination.

[01:32:23]Surface reflectance and sensor sensitivity.

[01:32:38]Bro, please let's be professional here.

[01:32:40]This is not a personal meet on. This is just for academical purposes.

[01:32:54][snorts] Identify the purpose of camera calibration.

[01:33:13]Identify the purpose of camera calibration in imaging systems.

[01:33:25]Identify the purpose of camera calibration in imaging systems. Identify the purpose of camera calibration in imaging systems for two marks.

[01:33:59]Camera calibration is the process of determining the internal and external parameters.

[01:34:23]of a camera system to accurately map 3D world coordinates high power mu2 coordinates to 2D Camera calibration is the process of determining the internal No, I don't know.

[01:35:03]Camera calibration is the process of determining the internal and external parameters of a camera system to accurately map 3D world coordinates onto 2D world pixels.

[01:35:19]Parameters of camera system.

[01:35:25]Meetric reconstruction.

[01:35:39][snorts] It allows the system.

[01:35:46]It allows the system to relate pixel distances to real world units.

[01:36:10]Example, mm enabling accurate [laughter] 3D measurements and depth estimation.

[01:36:45]distortion correction.

[01:36:51]It identifies and compensates for lens distortions.

[01:37:08]radial and tangential ensuring the straight lines in the real world appear straight. Eight.

[01:37:58]I guess my highest GPA is 9.6 six in my second semester.

[01:38:15]These two characteristics of perspective projection used in camera models. In camera models, perspective projection mimics how the human eye and real world cameras perceive 3D objects on a 2D plane. Two fundamental characteristics include vanishing points. Parallel lines in 3D space that are not parallel to the image plane appear to converge at a single point the vanishing point.

[01:38:38]Parallel lines in 3D space that are not parallel to the image plane appear to converge at a single point the vanishing point in the 2D image. Size dimution.

[01:38:48]The size of an object's projection is inversely proportional to the distance from the camera. The size of an object's projection is inversely proportional to the distance from the camera.

[01:39:00]State the purpose of object recognition in computer vision applications. The primary purpose of object recognition in computer vision is to enable a system to identify and to both identify and locate spec specific objects within an image or video stream. Classification assigning a label to an object. Example, identifying that a group of pixels represents a car or a person. Localization determining the exact position and boundaries of that object within the visual field often represented by a bounding box. [snorts] Define lens distortion and image processing. Lens distortion is an optical aberration made a camera lens fails to project.

[01:39:48]Lens distortion is an optical abrasion where a camera lens fails to project straight lines in the physical world as straight lines in an image. Image processing is the use of computer algorithms to perform operations or is an is an optical aberration where a camera lens fails to project straight lines in the physical world as straight lines in an image.

[01:40:19]I don't know maybe it can or maybe it cannot. If you have very good skills and know how to use AI well, you should be fine.

[01:40:34]It has already started taking jobs of many people. It will not completely take jobs but what it does is that it reduces the people required. So if a company usually hires 20 to 30 people now using AI it will only take four to five people using AI one person needs to do the work of 10 people. So if you have very good skills you should be in that you can be in those one to four people.

[01:41:29]Define the term feature detection in computer vision.

[01:41:33]Feature detection is the process of identifying interest points or localized structures in an image that contain significant information for analysis.

[01:41:43]Key properties. Features must be invariant and changing to transformations like scaling, rotation, and illumination types. Common features include edges, intensity, gradients, corners, junctions of edges and blocks, regions of uniform intensity. List the applications of computer vision any autonomous vehicles.

[01:42:03]Realtime detection of traffic signs lanes and obstacles for navigation.

[01:42:07]Medical imaging. Automated diagnosis of tumors or fractures from X-rays and biometric security, facial recognition for identity verification and surveillance, medical imaging, autonomous vehicles, biometric security and industrial inspection, automated quality controls to detect defect to detect defects in manufacturing lanes.

[01:42:28]Ident define the term image processing.

[01:42:30]Image processing is the use of computer algorithms to perform mathematical operations on a digital image is the use of computer algorithms to perform mathematical operations on a digital image to enhance its quality or extract meaningful information. Define lens distortion in image processing. Lens distortion often referred to as geometric distortion is an optical aberration where the linear mapping between optical aberration where the linear mapping between the 3D scene and 2D plane is physically bared by the camera lens.

[01:43:02]Optical operation where the linear mapping between the 3D scene and the 2D plane is physically marked by the camera lens. It is characterized by two primary types radial distortion which consists of barrel and pin cushion. Then tangential discussion. What is a syntactic recognition? Syntactic or structural recognition is a pattern recognition method that describes convex objects through their hierarchal structure that describes convex objects through the hierarchal structure or the relationship between simpler components or the relationship between simpler components. Primitives decomposes a pattern into basic building blocks called primitives. Examples um can be edges, arcs, lines or shapes.

[01:43:48]Grammar based. It uses it uses formal grammars rules to define how these primitives must be arranged or corrected to represent a specific object class.

[01:43:58]Define [snorts] the term feature extraction and computer vision.

[01:44:00]Differentiate between object detection and image classification. Feature image classification. Object detection. Goal identify what is the image. Identifies what and where it is. So image classification just identifies what is in the image. Whereas object classification identifies what is in the image, what are there in the image and where are they located. The output is single class label for the entire image and it class labels plus bounding boxes for multiple objects.

[01:44:29]Describe the pinhole camera model used in computer vision. The pinhole camera model is a mathematical description is a mathematical description that maps 3D points from the real world onto a 2D image plane through a single point called aperture or optical center through a single point called aperture.

[01:44:47]So what a pinhole camera is a pinhole camera is a mathematical description that maps 3D points from the real world onto a 2D plane using a single point called aperture or optical center x which goes by the formula x= f of xyz y= small y of capital y by z f of identify two factors affecting phototric image formation. Phototric formation describes how light intensity is captured as pixel values. Phototric formation describes how light intensity is captured as pixel values. Illumination the intensity position and color color of the light sources striking the object.

[01:45:29]Reflectance. Albido the material property of the surface that determines how much light the material property of the surface that determines how much light is reflected toward the sensor that is diffused versus specular.

[01:45:43]List two properties of fn transformation in image geometry. Linearity and parallelism.

[01:45:50]Image geometry. Fn transformations.

[01:45:52]Straight lines remain straight lines and parallel lines in the original image.

[01:45:56]Parallel lines after transformation.

[01:45:58]Ratio of distances while lengths and angles may change. The range lengths and angles may change. The ratio of lens along a straight line segment is preserved.

[01:46:12]I think even if it does take jobs in future, it could never take mine because I feel like AI is so dumb because AI never defeated me in tic tac toe that in very hard level. I'm too smart to be defeated.

[01:46:28]Congratulations for you if you feel that way. All the best for your future too.

[01:46:33]So we have completed our second session right now. We have successfully completed our two sessions today for of 40 minutes.

[01:46:42]So right now we'll be going to the Q&A session. If you have any questions or if you have any suggestions or if you have anything at all just drop it in the comments. We'll interact for 10 minutes and then we'll wrap up the session for today. How is the session today? What did you feel of today's session? Can I get the feedback from the people who are watching?

[01:47:30]>> [snorts] >> So tell me how did the session? go today. What did you study? Did you complete your goals for today's session?

[01:47:47]We'll have a 5 to 10 minute Q&A session and then we'll wrap this today.

[01:47:53]I successfully completed 16 questions today. Just 16 for two hours.

[01:48:06]1 hour 40 40 80 1 hour 20 minutes for 16 minutes I 16 questions I which is very less because I kept interacting with you guys but anyway better than nothing so if you're watching this live please drop your feedback or if you completed your goals or if you have any questions at all then we'll wrap the session.

[01:48:54]So we could interact in this 10-minute session.

[01:49:26]whenever you I'm not going to acknowledge this.

[01:50:02]This is a very So yeah, please study with me tomorrow.

[01:50:34]Pawan, bring your books and your syllabus. Uh if you have your exams, sit with this live in front of me. Use Pomoro technic study. As long as I study, take a break. When I take a break, did you complete your goals for today?

[01:50:59]If you have studied anything or if you have any questions or any doubts or anything at all, if you want to say anything, just drop it in the live chat.

[01:51:25]I did reply you. So bring bring your subjects and study with me. I I replied you. Please go back and check it.

[01:51:38]We just have two minutes to hit two hours.

[01:51:42]Live time means uh we'll do two lives tomorrow. It will be one in the morning or evening and then one at night.

[01:52:01]We'll have two sessions tomorrow as I told earlier. It will be from morning or evening and then one at the night.

[01:52:35]Whatever feels good to you, please go on Krishna. Hi.

[01:52:44]You join at the end of the live session when we are about to wrap up.

[01:52:51]Join early tomorrow.

[01:53:24]So I think we are going to wrap up the session. We hit the 2our mark that is why I was waiting and then if you have anything else right now please drop it right now or we'll wrap up the session.

[01:53:37]Okay. So nice seeing you all study with me. I had an amazing session today.

[01:53:42]We'll continue the live tomorrow.

[01:53:46]All the best Krishna for your MSET exam.

[01:53:50]So I'm going to wrap this live right now. Get to join tomorrow at the same timings and we'll have two lives tomorrow. One in the morning, evening, morning or evening and then one at the night.

[01:54:01]So yeah, thanks for joining me. If you have any questions right now, please drop it. Otherwise, we'll wrap the session up.

[01:54:10]Okay, then. See you all tomorrow. Bye.

[01:54:13]Nice meeting you all.