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» Detecting Occlusion for Hidden Markov Modeled Shapes
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CVPR
1999
IEEE
16 years 4 months ago
Generic Object Detection using Model Based Segmentation
This paper presents a novel approach for detection and segmentation of generic shapes in cluttered images. The underlying assumption is that generic objects that are man made, fre...
Zhiqian Wang, Jezekiel Ben-Arie
ICPR
2004
IEEE
16 years 3 months ago
Complex Human Activity Recognition for Monitoring Wide Outdoor Environments
The problem of automatic recognition of human activities is among the most important and challenging open areas of research in Computer Vision. This paper presents a new approach ...
Arcangelo Distante, I. Gnoni, Marco Leo, Paolo Spa...
EMNLP
2004
15 years 3 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
ECCV
2006
Springer
16 years 3 months ago
Detecting Instances of Shape Classes That Exhibit Variable Structure
This paper proposes a method for detecting instances of shape classes that exhibit variable structure. The term "variable structure" is used to characterize shape classes...
Vassilis Athitsos, Jingbin Wang, Stan Sclaroff, Ma...
CVPR
2004
IEEE
16 years 4 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong