Sciweavers

39 search results - page 1 / 8
» Jensen-Shannon Boosting Learning for Object Recognition
Sort
View
CVPR
2005
IEEE
13 years 10 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
SCIA
2005
Springer
174views Image Analysis» more  SCIA 2005»
13 years 9 months ago
Object Localization with Boosting and Weak Supervision for Generic Object Recognition
Abstract. This paper deals, for the first time, with an analysis of localization capabilities of weakly supervised categorization systems. Most existing categorization approaches ...
Andreas Opelt, Axel Pinz
ECCV
2004
Springer
14 years 6 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
ECCV
2006
Springer
14 years 6 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...
PAMI
2006
185views more  PAMI 2006»
13 years 4 months ago
Generic Object Recognition with Boosting
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...