RBT337 Final Project: Augmented Reality Pong

Dan Willinger is back with his final project for RBT337 - Digital Vision and Sensor Processing.  Using OpenCV, Dan implemented an augmented reality Pong clone that tracks the size and location of two white objects (pens in the demo video) that act as the paddles in the game.  Also, the length of the white object can change the size of the paddle.

RBT337 Final Project: Face Recognition

A demonstration of the final project for my course RBT337 - Digital Vision and Sensor Processing by Brittany Wilkerson and Casey Johnson. Their final project used OpenCV's face detection and SURF algorithm to identify faces in a live video feed.

RBT337 Final Project: Glyph Tracking

Mike's back, demonstrating his final project for UAT's Digital Vision and Sensor Processing course. In this video, Mike is demonstrating his SURF-based Glyph tracking system. Take it away Mike!

RBT337 Final Project: Connect 4

For their semester project in UAT's Digital Vision and Sensor Processing course, Josh Butler and Mark Stoddard implemented an excellent Connect 4 augmented reality program that warns a user if 3 pieces of the same color are placed in a row by highlighting the warning area in green. If a set of 3 is blocked, it is eliminated as a possible "win."

This first video shows the program in operation, live, raw video in the top left, augmented video in the bottom left, and color filters on the right for red and black pieces.



This second video demonstrates some of the inner workings of the program.

The bottom left pane now shows how the program scans over the all of the possible positions in the live feed, determining if the location contains a red or black piece, or is empty. This information is used to populate an array internally, which is then checked for "3 in a row."

RBT337 - Optical Flow

This is another assignment in UAT's Digital Vision and Sensor Processing course. In this laboratory, students are tasked with implementing and comparing optical flow algorithms, one using Lucas Kanade, and another using SURF.

Here is Mike Peters demonstrating optical flow using the Lucas Kanade algorithm:


And the SURF Algorithm:

RBT337 - Object Tracking

As one of the laboratory assignments in the UAT Digital Vision and Sensor Processing course, students implement the OpenCV SURF algorithm on a live video feed.  Here are some example videos of what my students produced. In the videos, the white lines indicate the tracking of matched features in one image (usually a target) to another (the live video).


(By Josh Butler)


(By Leonard Hockett)


(By Ryan Carmain)


(By Mike Peters)