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» Multiple Component Learning for Object Detection
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ACCV
2006
Springer
15 years 3 months ago
Fusion of 3D and Appearance Models for Fast Object Detection and Pose Estimation
Real-time estimation of a camera’s pose relative to an object is still an open problem. The difficulty stems from the need for fast and robust detection of known objects in the s...
Hesam Najafi, Yakup Genc, Nassir Navab
CVPR
2010
IEEE
14 years 9 months ago
Scene understanding by statistical modeling of motion patterns
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of pattern...
Imran Saleemi, Lance Hartung, Mubarak Shah
83
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ECCV
2010
Springer
14 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ECCV
2010
Springer
15 years 1 months ago
Cascaded Confidence Filtering for Improved Tracking-by-Detection
We propose a novel approach to increase the robustness of object detection algorithms in surveillance scenarios. The cascaded confidence filter successively incorporates constraint...
ECCV
2008
Springer
15 years 11 months ago
Face Alignment Via Component-Based Discriminative Search
In this paper, we propose a component-based discriminative approach for face alignment without requiring initialization1 . Unlike many approaches which locally optimize in a small ...
Lin Liang, Rong Xiao, Fang Wen, Jian Sun