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» Graph-Theoretical Methods in Computer Vision
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CVPR
2006
IEEE
16 years 9 months ago
Intelligent Collaborative Tracking by Mining Auxiliary Objects
Many tracking methods face a fundamental dilemma in practice: tracking has to be computationally efficient but verifying if or not the tracker is following the true target tends t...
Ming Yang, Ying Wu, Shihong Lao
ICCV
2007
IEEE
16 years 9 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan
ACIVS
2006
Springer
16 years 1 months ago
A Linear-Time Approach for Image Segmentation Using Graph-Cut Measures
Abstract. Image segmentation using graph cuts have become very popular in the last years. These methods are computationally expensive, even with hard constraints (seed pixels). We ...
Alexandre X. Falcão, Paulo A. V. Miranda, A...
ICPR
2010
IEEE
15 years 11 months ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking me...
Gustavo Carneiro, Jacinto Nascimento
ICCTA
2007
IEEE
16 years 1 months ago
Stabilisation of Active Contours Using Tangential Evolution: An Application to Tracking
— Active contours are very widely used in computer vision problems. Their usage has a typical problem, that of bunching together of curve points. This becomes apparent especially...
Viswanathan Srikrishnan, Subhasis Chaudhuri, Suman...