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» Unsupervised Learning of Invariant Features Using Video
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ALT
2006
Springer
14 years 4 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
FGR
2008
IEEE
208views Biometrics» more  FGR 2008»
14 years 2 months ago
Unsupervised learning from local features for video-based face recognition
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
Ajmal Mian
ICIP
2008
IEEE
14 years 9 months ago
Activity-based temporal segmentation for videos of interacting objects using invariant trajectory features
This paper presents a content-based approach for temporal segmentation of videos. Tracked objects are characterized by their 2D trajectories which are used in a meaningful way to ...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
CVPR
2009
IEEE
1848views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Moving Cast Shadow Detection using Physics-based Features
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...
Jia-Bin Huang and Chu-Song Chen
IV
2007
IEEE
222views Visualization» more  IV 2007»
14 years 1 months ago
Video Stabilization Using Scale-Invariant Features
Video Stabilization is one of those important video processing techniques to remove the unwanted camera vibration in a video sequence. In this paper, we present a practical method...
Rong Hu, Rongjie Shi, I-Fan Shen, Wenbin Chen