Larry S. Davis

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Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can handle situations where the background of the scene is cluttered and(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)
ÐW 4 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. W 4 employs a combination of shape analysis and tracking to locate people and their parts (head, hands, feet,(More)
A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More(More)
A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More(More)
In this paper, we describe a method for finding the pose of an object from a single image. We assume that we can detect and match in the image four or more noncoplanar feature points of the object, and that we know their relative geometry on the object. The method combines two algorithms; the first algorithm,POS (Pose from Orthography and Scaling)(More)
This paper presents a novel algorithm for detecting moving objects from a static background scene that contains shading and shadows using color images. We develop a robust and e ciently computed background subtraction algorithm that is able to cope with local illumination changes, such as shadows and highlights, as well as global illumination changes. The(More)
Appearance information is essential for applications such as tracking and people recognition. One of the main problems of using appearance-based discriminative models is the ambiguities among classes when the number of persons being considered increases. To reduce the amount of ambiguity, we propose the use of a rich set of feature descriptors based on(More)
We describe new techniques to detect and analyze periodic motion as seen from both a static and moving camera. By tracking objects of interest, we compute an object’s self-similarity as it evolves in time. For periodic motion, the self-similarity measure is also periodic, and we apply Time-Frequency analysis to detect and characterize the periodic motion.(More)