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CVPR
2012
IEEE
13 years 9 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
ICDAR
2009
IEEE
16 years 1 months ago
Learning and Adaptation for Improving Handwritten Character Recognizers
Writer independent handwriting recognition systems are limited in their accuracy, primarily due the large variations in writing styles of most characters. Samples from a single ch...
Naveen Chandra Tewari, Anoop M. Namboodiri
RE
2007
Springer
16 years 27 days ago
Value-Based Requirements Traceability: Lessons Learned
Abstract. Traceability from requirements to code is mandated by numerous software development standards. These standards, however, are not explicit about the appropriate level of q...
Alexander Egyed, Paul Grünbacher, Matthias He...
WACV
2005
IEEE
16 years 11 days ago
Learning to Track Objects Through Unobserved Regions
As tracking systems become more effective at reliably tracking multiple objects over extended periods of time within single camera views and across overlapping camera views, incre...
Chris Stauffer
CVPR
2008
IEEE
15 years 8 months ago
Loose shape model for discriminative learning of object categories
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Margarita Osadchy, Elran Morash