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» A New Method for Auto-calibrated Object Tracking
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ICIP
2006
IEEE
15 years 11 months ago
Knowledge-Based Supervised Learning Methods in a Classical Problem of Video Object Tracking
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...
ICASSP
2011
IEEE
14 years 1 months ago
Video object tracking with differential Structural SIMilarity index
The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared ...
Artur Loza, Fanglin Wang, Jie Yang, Lyudmila Mihay...
ICIP
2009
IEEE
14 years 7 months ago
Object tracking by bidirectional learning with feature selection
This paper proposes a new tracking algorithm which combines object and background information, via building object and background appearance models simultaneously by nonparametric...
Heng Wang, Xinwen Hou, Cheng-Lin Liu
ICCV
2009
IEEE
14 years 7 months ago
Video object segmentation by tracking regions
This paper presents an approach to unsupervised segmentation of moving and static objects occurring in a video. Objects are, in general, spatially cohesive and characterized by lo...
William Brendel, Sinisa Todorovic
CVPR
2012
IEEE
12 years 12 months ago
Locally Orderless Tracking
Locally Orderless Tracking (LOT) is a visual tracking algorithm that automatically estimates the amount of local (dis)order in the object. This lets the tracker specialize in both...
Shaul Oron, Aharon Bar-Hillel, Dan Levi, Shai Avid...