Object Tracking & Understanding
Object tracking is important because it enables several important applications such as: Security and surveillance - to recognize people, to provide better sense of security using visual information; Medical therapy - to improve the quality of life for physical therapy patients and disabled people; Retail space instrumentation - to analyze shopping behavior of customers, to enhance building and environment design; Video abstraction - to obtain automatic annotation of videos, to generate object-based summaries; Traffic management - to analyze flow, to detect accidents; Video editing - to eliminate cumbersome human-operator interaction, to design futuristic video effects; Interactive games -Â to provide natural ways of interaction with intelligent systems such as weightless remote control.
Background & Objective: The current object tracking project has four main components: 1) Adaptive background generation and shadow removal; 2) Single-camera tracking with mean-shift techniques; 3) Multi-camera radiometric calibration; 4) Gesture recognition, object-based summary generation using multi-camera tracking information. Accurate object segmentation and tracking under the constraint of low computational complexity presents a challenge. Our aim is to find solutions that are robust, simple, computationally feasible, modular, and easily adaptable to various applications.
Technical Discussion: We made the semi-automatic mean-shift tracker completely automatic using an improved GMM background subtraction method. We improved the adaptation performance of the original GMM by observing the amount of illumination change in the background. The performance of the background adaptation and mean-shift analysis based object tracking method is comparable with the state-of-art, and it is fully automatic. We invented solution to the inter-camera color calibration problem, which is very important for multi-camera systems. We also introduced a distance metric and a modeling function to evaluate the inter-camera radiometric properties.
Contact: Fatih Porikli
Technology Area: Computer Vision
Modification Date: July 15, 2004