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» Urban Object Recognition from Informative Local Features
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SSPR
2010
Springer
14 years 10 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 6 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
15 years 1 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 7 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 4 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...