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Background subtraction is a method typically used to segment m o ving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a n o vel non-parametric background model and a background subtraction approach. The model can handle situations where the background of the scene is cluttered(More)
Ї R is a real time visual surveillance system for detecting and tracking multiple people and monitoring their activities in an outdoor environment. It operates on monocular gray-scale video imagery, or on video imagery from an infrared camera. ‡ R employs a combination of shape analysis and tracking to locate people and their parts (head, hands, feet,(More)
Invited Paper Automatic understanding of events happening at a site is the ultimate goal for many visual surveillance systems. Higher level understanding of events requires that certain lower level computer vision tasks be performed. These may include detection of unusual motion, tracking targets, labeling body parts, and understanding the interactions(More)
We present a real-time algorithm for foreground–background segmentation. Sample background values at each pixel are quantized into codebooks which represent a compressed form of background model for a long image sequence. This allows us to capture structural background variation due to periodic-like motion over a long period of time under limited memory.(More)
We present a new fast algorithm for background modeling and subtraction. Sample background values at each pixel are quantized into codebooks which represent a compressed form of background model for a long image sequence. This allows us to capture structural background variation due to periodic-like motion over a long period of time under limited memory.(More)
W 4 is a real time visual surveillance system for detecting and tracking people and monitoring their activities in an outdoor environment. It operates on monocular grayscale video imagery, or on video imagery from an infrared camera. Unlike many of systems for tracking people, W 4 makes no use of color cues. Instead, W 4 employs a combination of shape(More)
Significant research has been devoted to detecting people in images and videos. In this paper we describe a human detection method that augments widely used edge-based features with texture and color information, providing us with a much richer descriptor set. This augmentation results in an extremely high-dimensional feature space (more than 170,000(More)
Ghost is a real time system for estimating human body posture and detecting body parts in monochro-matic imagery. It constructs a silhouette based b ody model to determine the location of the body parts while people are in generic postures. It combines hierarchical body pose estimation, a convex hull analysis of the silhouette, and a partial mapping from(More)
Detecting vehicles in aerial images has a wide range of applications, from urban planning to visual surveillance. We describe a vehicle detector that improves upon previous approaches by incorporating a very large and rich set of image descriptors. A new feature set called Color Probability Maps is used to capture the color statistics of vehicles and their(More)