Human Robot Vision Network

Automated visual scene understanding has remained a very hard problem for uncontrolled environments. For the foreseeable future, it is natural to expect that humans and computer vision systems will be working together in applications like disaster response. This project explores the fundamental scientific challenges in the coordination between humans and robots for tasks in computer vision and robotics. More...


Camera Networks

Networks of cameras are nowadays installed in various places. However, most of the data collected by such networks are analyzed manually, thus severely limiting their application. In this research, which is divided into different sub-projects, we are studying the core scientific and technical issues related to camera networks, such as information fusion, network control, activity analysis, the interplay between networking and computer vision, and computational complexity. More...


Wide Area Scene Analysis

Video-based analysis of large areas and long time periods is a very challenging problem because of the need to maintain long-term stability of the tracks and understand the spatio-temporal behavior patterns. In this research, we will be developing algorithms for tracking and activity analysis in camera networks covering a large area. More...


Activity Recognition

The goal of this project is to retrieve segments from a video database given a video clip of an activity of interest. Not only does this require development of activity recognition algorithms, these algorithms need to be integrated with video search and retrieval methods in large databases. More...


Face Recognition

Face recognition continues to be one of the important problems in computer vision. Our goal is to develop video-based face tracking and recognition algorithms that are robust to changes of pose and lighting. More...


Biological Image Analysis

The goal of this project is identification, spatio-temporal modeling and recognition of dynamical patterns inherent in developmental biology through the use of novel computational tools in image analysis, statistical data aggregation, pattern recognition, machine learning and dynamical modeling. This will lead to the development of new methods for addressing some outstanding challenges in this area, i.e., computing cell lineages, identifying long-term patterns in the tracked output and learning functional models of the dynamics of cell growth and division. More...


VideoWeb: A Video Network Lab

This unique facility will consist of about 80 video cameras, a few infra-red cameras, and a collection of acoustic, seismic and vibration sensors connected through a wireless network in an outdoor environment. This will enable researchers to work on the problems at the intersection of a number of diverse disciplines, like computer vision and image processing, networking, communications, databases, and others. More...


Multi-terminal Video Compression

This work focuses on developing a distributed video compression algorithm that exploits the redundancy in data captured from multiple overlapping cameras, with minimal communication between the sensors. More...