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IJPRAI
2002
97views more  IJPRAI 2002»
13 years 8 months ago
Shape Description and Invariant Recognition Employing Connectionist Approach
This paper presents a new approach for shape description and invariant recognition by geometric-normalization implemented by neural networks. The neural system consists of a shape...
Jezekiel Ben-Arie, Zhiqian Wang
PAMI
2008
235views more  PAMI 2008»
13 years 7 months ago
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
ECCV
2010
Springer
13 years 6 months ago
Discriminative Nonorthogonal Binary Subspace Tracking
Visual tracking is one of the central problems in computer vision. A crucial problem of tracking is how to represent the object. Traditional appearance-based trackers are using inc...
Ang Li, Feng Tang, Yanwen Guo, Hai Tao
COGCOM
2010
107views more  COGCOM 2010»
13 years 5 months ago
Where to Look Next? Combining Static and Dynamic Proto-objects in a TVA-based Model of Visual Attention
To decide ``Where to look next ?'' is a central function of the attention system of humans, animals and robots. Control of attention depends on three factors, that is, lo...
Marco Wischnewski, Anna Belardinelli, Werner X. Sc...
TIP
2011
217views more  TIP 2011»
13 years 3 months ago
Contextual Object Localization With Multiple Kernel Nearest Neighbor
—Recently, many object localization models have shown that incorporating contextual cues can greatly improve accuracy over using appearance features alone. Therefore, many of the...
Brian McFee, Carolina Galleguillos, Gert R. G. Lan...