Recent Mentions
Real-Time Augmented Reality in Live Football Broadcasts
L. Gentry and R. Parker, "Real-Time Augmented Reality in Live Football Broadcasts", San Francisco Bay ACM, 2016.Sportvision, ESPN Successfully Deploy 1st & Ten Line on Monday Night Football Spidercam
J. Dachman, "Sportvision, ESPN Successfully Deploy 1st & Ten Line on Monday Night Football Spidercam", Sports Video Group, 2015.Guided Depth Enhancement via a Fast Marching Method
X. Gong, J. Liu, W. Zhou, and J. Liu. "Guided depth enhancement via a fast marching method", Image and Vision Computing, 31(10):695–703, Oct. 2013.Guided Depth Enhancement via Anisotropic Diffusion
J. Liu and X. Gong. "Guided depth enhancement via anisotropic diffusion", Advances in Multimedia Information Processing - PCM 2013, volume 8294 of Lecture Notes in Computer Science, pages 408–417. Springer International Publishing, 2013.Development of a Computer Vision System for the Blind and Visually Impaired Person
R. A. Maao. "Development of a computer vision system for the blind and visually impaired person." International Journal of Computer, Information, Systems and Control Engineering, 7(11):804–808, 2013.Gender Recognition Using Neural Networks and ASR Techniques
J. Sas and A. Sas. "Gender recognition using neural networks and asr techniques." Journal of Medical Informatics & Technologies, 22, 2013.-->Projects
Real-Time Kinect Player Gender Recognition from Speech
I have developed an algorithm that determines a player's gender using speech analysis. When a player enters the scene, they are required to speak a short utterance. In real time, that player's gender is then determined and their skeleton is assigned the corresponding color.
Project PDF » Project Powerpoint » Demo Male » Demo Female »Monocular Occlusion-Based Video Segmentation
with: Ahmad Humayun
This project altered the state-of-the-art video segmentation by providing pixel-wise occlusion probabilities as a cue in the oversegmentation stage. We evaluate our algorithm by comparing to both the original video segmentation and the Depth-Based Hierarchical Video Segmentation project also mentioned on this page.
Depth-Based Hierarchical Video Segmentation
with: Ahmad Humayun and Matthias Grundmann
For this project, we used the depth sensor from an XBOX Kinect to serve as an extra region feature in the state-of-the-art RGB video segmentation. We compared various depth descriptors and distance metrics to serve as extra terms in the region edge weight formulation.
XBOX Kinect Depth Map Inpainting and Filtering
with: Denis Aleshin and Kevin Hampton
In our project we implemented a package that will make use of the underlying color and temporal information to inpaint holes and stabilize edges, thus preparing the depth information for further applications in computer vision.
Embedded Human Projector Pong
with: Shruti Bhagat, Sohil Mehta, and Priti Marappan
During my first semester as a graduate student, I worked on a human-interactive projector pong-like game. Using a simple handheld blue LED, players stand in front of a webcam/projector set-up and control their paddles in the game according to the location of the LED. The system was deployed on an embedded system with a micro-projector to allow for mobile gameplay wherever a power outlet exists.
Automated Security System for Boat Owners
with: David Salazar, Rohit Sahay, Ramsey Baker, and Kunal Parbadia
For my final semester of my undergraduate work at Georgia Tech, I worked on a luxury yacht surveillance and monitoring system. Essentially, the system utilizes an iPhone application that notifies the user when any type of motion has been detected in the boat’s cabin or if flooding has been detected in the boat’s hull. This system can be remotely controlled and requires no human interaction once initially configured.