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CVPR
2009
IEEE
16 years 12 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
ICCV
2009
IEEE
1042views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Activity Recognition using the velocity histories of tracked keypoints
We present an activity recognition feature inspired by human psychophysical performance. This feature is based on the velocity history of tracked keypoints. We present a generat...
Ross Messing, Chris Pal, Henry Kautz
ICCV
2009
IEEE
2030views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Robust Tracking-by-Detection using a Detector Confidence Particle Filter
We propose a novel approach for multi-person trackingby- detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
CVPR
1997
IEEE
16 years 6 months ago
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
Shape indexing is a way of making rapid associations between features detected in an image and object models that could have produced them. When model databases are large, the use...
Jeffrey S. Beis, David G. Lowe
CVPR
2003
IEEE
16 years 6 months ago
Practical Super-Resolution from Dynamic Video Sequences
This paper introduces a practical approach for superresolution, the process of reconstructing a high-resolution image from the low-resolution input ones. The emphasis of our work ...
Zhongding Jiang, Tien-Tsin Wong, Hujun Bao
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