Detection and location of people in video images using adaptive fusion of color and edge information

By S. Jabri, Zoran Duric, Harry Wechsler, Azriel Rosenfeld. Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2000

294 citations recorded by the source corpus.

A new method of finding people in video images is presented. The detection is based on a novel background modeling and subtraction approach which uses both color and edge information. We introduce confidence maps gray-scale images whose intensity is a function of confidence that a pixel has changed - to fuse intermediate results and represent the results of background subtraction. The latter is used to delineate a person's body by guiding contour collection to segment the person from the background. The method is tolerant to scene clutter, slow illumination changes, and camera noise, and runs in near real time on a standard platform.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/13bdec73574822d75140dd2cf1c47ea5848011b5

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In Computer Vision and Pattern Recognition

Citations in the corpus

Video Processing From Electro-Optical Sensors for Object Detection and Tracking in a Maritime Environment: A Survey (2016, methodology): “Similar idea was employed in [68], [69], where, instead of the relaxation function used in [29], confidence maps [68] and chi-squared measure of similarity [69] were used to segment the image into background and foreground regions.”
A texture-based method for modeling the background and detecting moving objects (2006, methodology): “Unlike most other approaches, the features in background modeling are”
Background and foreground modeling using nonparametric kernel density estimation for visual surveillance (2002, methodology): “A fusion of intensity and edge information was used in [16].”
Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art (2008, background): “Actually, most of the background models are built on a set of initial parameters that comes out from a short sequence, in which no foregrounds objects are present [112].”
Detecting Moving Objects, Ghosts, and Shadows in Video Streams (2003, unknown): “D ETECTION of moving objects in video streams is the first relevant step of information extraction in many computer vision applications, including video surveillance, people tracking, traffic monitoring, and semantic annotation of videos.”