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» A Novel Clustering-Based Method for Adaptive Background Segm...
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87
Voted
ICIP
2006
IEEE
16 years 1 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
104
Voted
CVPR
2006
IEEE
15 years 5 months ago
3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera
We present a novel method to obtain a 3D Euclidean reconstruction of both the background and moving objects in a video sequence. We assume that, multiple objects are moving rigidl...
Chang Yuan, Gérard G. Medioni
CVPR
2007
IEEE
15 years 3 months ago
Inferring 3D Volumetric Shape of Both Moving Objects and Static Background Observed by a Moving Camera
We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that th...
Chang Yuan, Gérard G. Medioni
250
Voted
CVPR
2012
IEEE
13 years 5 months ago
Foreground Detection Using Spatiotemporal Projection Kernels
Foreground detection is at the core of many video processing tasks. In this paper, we propose a novel video foreground detection method that exploits the statistics of 3D space-tim...
Y. Moshe, H. Hel-Or, and Y. Hel-Or
CVPR
2008
IEEE
16 years 1 months ago
Stereo reconstruction with mixed pixels using adaptive over-segmentation
We present an over-segmentation based, dense stereo algorithm that jointly estimates segmentation and depth. For mixed pixels on segment boundaries, the algorithm computes foregro...
Yuichi Taguchi, Bennett Wilburn, C. Lawrence Zitni...