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» Likelihood Map Fusion for Visual Object Tracking
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CVPR
2008
IEEE
14 years 9 months ago
Granularity and elasticity adaptation in visual tracking
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
Ming Yang, Ying Wu
ICCV
2003
IEEE
14 years 9 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
14 years 1 months ago
A New Approach to the Use of Edge Extremities for Model-based Object Tracking
— This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update sche...
Youngrock Yoon, Akio Kosaka, Jae Byung Park, Avina...
ICRA
2009
IEEE
173views Robotics» more  ICRA 2009»
14 years 2 months ago
Most salient region tracking
— In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to...
Simone Frintrop, Markus Kessel
TCSV
2011
13 years 2 months ago
Integrating Spatio-Temporal Context With Multiview Representation for Object Recognition in Visual Surveillance
—We present in this paper an integrated solution to rapidly recognizing dynamic objects in surveillance videos by exploring various contextual information. This solution consists...
Xiaobai Liu, Liang Lin, Shuicheng Yan, Hai Jin, We...