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...

Research Themes:

Active Learning
Camera Network Summarization

Wide Area Scene Analysis in Vision 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...

Research Themes:

Camera Network Tracking and Re-identification
Distributed Estimation
Active Sensing

Activity Recognition and Prediction

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...

Research Themes:

Activity Forecasting
Context-Aware Activity Recognition

Situational Awareness Under Resource Constraints

The goal of this project is to facilitate the timely retrieval of dynamic situational awareness information from field deployed information-rich sensors by an operational center in disaster recovery or search and rescue missions, which are typically characterized by resource-constrained uncertain environments. More...

Research Themes:

Video Analysis under Resource Constraints

Face Tracking and 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...

Research Themes:

Face Recognition in Art Images
Face Tracking and Recognition in Video

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...

Research Themes:

Cell Tracking and Shape Modeling

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...