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» Urban Object Recognition from Informative Local Features
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SSPR
2010
Springer
14 years 8 months ago
An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces
The aim of this paper is to find an answer to the question: What is the difference between dissimilarity-based classifications(DBCs) and other kernelbased classifications(KBCs)?...
Sang-Woon Kim, Robert P. W. Duin
IROS
2007
IEEE
157views Robotics» more  IROS 2007»
15 years 4 months ago
A spatio-temporal probabilistic model for multi-sensor object recognition
— This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations. The alg...
Bertrand Douillard, Dieter Fox, Fabio T. Ramos
ECAI
2008
Springer
14 years 11 months ago
Learning to Select Object Recognition Methods for Autonomous Mobile Robots
Selecting which algorithms should be used by a mobile robot computer vision system is a decision that is usually made a priori by the system developer, based on past experience and...
Reinaldo A. C. Bianchi, Arnau Ramisa, Ramon L&oacu...
WACV
2012
IEEE
13 years 5 months ago
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang
ICCV
2009
IEEE
1335views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Top-Down Color Attention for Object Recognition
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary cons...
Fahad Shahbaz Khan, Joost van de Weijer, Maria Van...