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» Learning Mid-Level Features For Recognition
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EPIA
2009
Springer
13 years 11 months ago
Semantic Image Search and Subset Selection for Classifier Training in Object Recognition
Abstract. Robots need to ground their external vocabulary and internal symbols in observations of the world. In recent works, this problem has been approached through combinations ...
Rui Pereira, Luís Seabra Lopes, Augusto Sil...
ICPR
2008
IEEE
14 years 9 months ago
Hand posture recognition with co-training
As an emerging human-computer interaction approachvision based hand interaction is more natural and efficient. Howeverin order to achieve high accuracy, most of the existing hand ...
Yikai Fang, Jian Cheng, Jinqiao Wang, Kongqiao Wan...
ICPR
2004
IEEE
14 years 8 months ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic
IJCNN
2000
IEEE
13 years 11 months ago
People Recognition and Pose Estimation in Image Sequences
This paper presents a system which learns from examples to automatically recognize people and estimate their poses in image sequences with the potential application to daily surve...
Chikahito Nakajima, Massimiliano Pontil, Tomaso Po...
AAAI
2006
13 years 9 months ago
The Role of Context in Head Gesture Recognition
Head pose and gesture offer several key conversational grounding cues and are used extensively in face-to-face interaction among people. We investigate how dialog context from an ...
Louis-Philippe Morency, Candace L. Sidner, Christo...