https://pvela.gatech.edu/classes/ 2026-04-08T21:55:09+00:00 https://pvela.gatech.edu/classes/ https://pvela.gatech.edu/classes/lib/exe/fetch.php?media=wiki:dokuwiki.svg text/html 2024-08-21T01:38:55+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_autonav&rev=1724204335&do=diff Vision-Based Autonomous Navigation of a Mobile Robot This module is really a blend of robotics and computer vision. We will be exploring different, reactive algorithms for performing collision free navigation through the world, and maybe even vision-based tracking of an specifically colored target. The baseline set of activities will rely on the $p_{goal}$$p_{gap}$$n_1 x + n_2 y = 0$$n_1 x + n_2 y > d_\tau$$\vec n = (n_1, n_2)$$2 d_\tau$$p_{past} = p_{gap} + 2 d_\tau \vec n$$d_\tau$ text/html 2024-08-21T01:38:55+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_classification&rev=1724204335&do=diff Image-Based Classification Classification involves obtaining a sample and determining to which class the sample belongs (from a finite set of classes). The simplest form of classification is binary classification, where you must determine whether it is of class A or class B. The task ultimately boils down to determining identifying features of each class that are distinct from each other, then using those features to define a selection or classification policy. Here, we will explore different… text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_detection&rev=1724204336&do=diff Object Detection Note: To be filled out on Friday or Saturday. * Boosting * Sliding window /* (1) object detector with boosting: http://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.html */ Module #1: Human Detection The classic human detection paper is by Dalal and Triggs, and it involves using the Histogram of Oriented Gradients (HOG) feature descriptor together with Support Vector Machines. It does quite well, though more modern and more expensive methods have s… text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_pcd&rev=1724204336&do=diff Point Clouds Processing and Interpretation 3D point cloud is a commonly used data in spatial modeling & understanding. Such a data can be captured from laser scanners, stereo camera, or structured-light cameras. Point cloud processing is essential for applications like self-driving cars, infrastructure inspection, construction modeling, etc.. text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_recognition&rev=1724204336&do=diff Object Recognition Object recognition is very similar to object classification, maybe even detection. It is quite sensible to ask: what is the difference between object classification and object recognition? Even I would say that I have trouble. One way that I like to think about it is that classification is more about differentiating instances that perhaps are clearly different (fork vs spoon vs knife, or cat vs dog vs face), whereas maybe recognition is more about differentiating objects wi… text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_surveillance&rev=1724204336&do=diff Surveillance System with a Static Camera This is a pretty classic computer vision problem that combines detection, tracking, filtering, recognition, and logical parsing together into one system whose objective is to make sense of the comings and goings of people or objects within a scene. It is one of the few of the modules that requires some nominal level of system integration to get running properly. Matlab has Simulink code that does this for the case of abandoned object detection, which is text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:module_tracking&rev=1724204336&do=diff Tracking THIS MODULE IS NOT AVAILABLE SINCE IT IS INCOMPLETE. Particle filter, Kalman Filter and face tracking Module #1 Particle filter * Study particle filter tutorial * Watch tutorial video part 1 * Watch tutorial video part 2 * Study Matlab implementation text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:modules&rev=1724204336&do=diff Listing of Learning Modules The objective of the learning modules is to explore some concept relative to computer vision that will not be covered in class. The area of computer vision is huge, and there is no way to cover it all in one semester. Given that these topics may not be fully covered in class, though individual aspects of some of them might be, it is important to pick a topic that you are interested in. The bulk of the learning will be done by you through the exploration of the topic… text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:questionsformative&rev=1724204336&do=diff ECE4580: Formative Questions The questions below are meant to highlight key aspects or principles related to the reading. Being able to answer them prior to the lectures of that week should provide you with some nominal uderstanding of what will be covered so that you may focus on understanding the material and listening, as opposed to the written material on the board. Some of the questions may be slight variations on each other. Many involve answering multiple questions, so maybe we should … text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:schedule&rev=1724204336&do=diff Progression of Course Material The schedule below roughly approximates the timeline of course material presentation. It ends a bit earlier than the course which means that (i) some of the material will take a little longer than indicated at the moment, and (ii) there may be some time to consider other aspects of computer vision.$SE(3)$$k$ text/html 2024-08-21T01:38:56+00:00 Anonymous (anonymous@undisclosed.example.com) https://pvela.gatech.edu/classes/doku.php?id=ece4580:start&rev=1724204336&do=diff ECE4580: Computational Computer Vision General resources for the class are: * [ Sample Syllabus] * Timeline * Learning Modules ---------- Main