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» Learning Boosted Asymmetric Classifiers for Object Detection
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ECCV
2008
Springer
13 years 9 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang
ECCV
2006
Springer
14 years 9 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
NIPS
2001
13 years 9 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
ICIP
2008
IEEE
14 years 9 months ago
Pedestrian detection via logistic multiple instance boosting
Pedestrian detection in still image should handle the large appearance and pose variations arising from the articulated structure and various clothing of human bodies as well as v...
Junbiao Pang, Qingming Huang, Shuqiang Jiang, Wen ...
CVPR
2001
IEEE
14 years 9 months ago
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...