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» A probabilistic framework for object recognition in video
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IWCM
2004
Springer
14 years 1 months ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
MM
2006
ACM
157views Multimedia» more  MM 2006»
14 years 1 months ago
Player action recognition in broadcast tennis video with applications to semantic analysis of sports game
Recognition of player actions in broadcast sports video is a challenging task due to low resolution of the players in video frames. In this paper, we present a novel method to rec...
Guangyu Zhu, Changsheng Xu, Qingming Huang, Wen Ga...
PAMI
2012
11 years 10 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
ATAL
2007
Springer
14 years 1 months ago
Towards using multiple cues for robust object recognition
A robot’s ability to assist humans in a variety of tasks, e.g. in search and rescue or in a household, heavily depends on the robot’s reliable recognition of the objects in th...
Sarah Aboutalib, Manuela M. Veloso
ECCV
2010
Springer
14 years 1 months ago
Dynamic Color Flow: A Motion-Adaptive Color Model for Object Segmentation in Video
Accurately modeling object colors, and features in general, plays a critical role in video segmentation and analysis. Commonly used color models, such as global Gaussian mixtures, ...