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» Combined visual attention model for video sequences
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ICPR
2010
IEEE
15 years 3 months ago
The Detection of Concept Frames Using Clustering Multi-Instance Learning
Abstract—The classification of sequences requires the combination of information from different time points. In this paper the detection of facial expressions is considered. Exp...
David Tax, Michel Valstar
3DPVT
2006
IEEE
204views Visualization» more  3DPVT 2006»
15 years 3 months ago
Multimodal 3D Shape Recovery from Texture, Silhouette and Shadow Information
Recent efforts attempt to combine together information of different passive methods. Critical issues in this research are the choice of data and how to combine such data in order ...
Luca Ballan, Guido Maria Cortelazzo
CVPR
1998
IEEE
15 years 11 months ago
Tracking People with Twists and Exponential Maps
This paper demonstrates a new visual motion estimation technique that is able to recover high degree-of-freedom articulated human body configurations in complex video sequences. W...
Christoph Bregler, Jitendra Malik
IVC
2008
203views more  IVC 2008»
14 years 9 months ago
Multi-modal tracking using texture changes
We present a method for efficiently generating a representation of a multi-modal posterior probability distribution. The technique combines ideas from RANSAC and particle filterin...
Christopher Kemp, Tom Drummond
WSCG
2001
110views more  WSCG 2001»
14 years 11 months ago
Moving Facial Image Transformations Based on Static 2D Prototypes
This paper describes a new method for creating visually realistic moving facial image sequences that retain an actor's personality (individuality, expression and characterist...
Bernard Tiddeman, David I. Perrett