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» Learning the Relative Importance of Features in Image Data
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178
Voted
CVPR
2012
IEEE
13 years 7 months ago
Geodesic flow kernel for unsupervised domain adaptation
In real-world applications of visual recognition, many factors—such as pose, illumination, or image quality—can cause a significant mismatch between the source domain on whic...
Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman
176
Voted
ECCV
2004
Springer
16 years 6 months ago
Extraction of Semantic Dynamic Content from Videos with Probabilistic Motion Models
Abstract. The exploitation of video data requires to extract information at a rather semantic level, and then, methods able to infer "concepts" from low-level video featu...
Gwenaëlle Piriou, Jian-Feng Yao, Patrick Bout...
CRV
2008
IEEE
295views Robotics» more  CRV 2008»
15 years 11 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
155
Voted
CVPR
2007
IEEE
16 years 6 months ago
Simultaneous Detection and Segmentation of Pedestrians using Top-down and Bottom-up Processing
We present a method for the simultaneous detection and segmentation of people from static images. The proposed technique requires no manual segmentation during training, and explo...
Vinay Sharma, James W. Davis
221
Voted
ICARCV
2006
IEEE
420views Robotics» more  ICARCV 2006»
15 years 10 months ago
Recognizing People's Faces: from Human to Machine Vision
— As confirmed by recent neurophysiological studies, the use of dynamic information is extremely important for humans in visual perception of biological forms and motion. Apart ...
Massimo Tistarelli, Manuele Bicego, Enrico Grosso