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» POP: Patchwork of Parts Models for Object Recognition
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CVPR
2011
IEEE
14 years 6 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
ICRA
2010
IEEE
153views Robotics» more  ICRA 2010»
14 years 8 months ago
High-speed 3D object recognition using additive features in a linear subspace
— In this paper we propose a method of high-speed 3D object recognition using linear subspace method and our 3D features. This method can be applied to partial models with any si...
Asako Kanezaki, Hideki Nakayama, Tatsuya Harada, Y...
ESSLLI
2009
Springer
14 years 7 months ago
A Salience-Driven Approach to Speech Recognition for Human-Robot Interaction
We present an implemented model for speech recognition in natural environments which relies on contextual information about salient entities to prime utterance recognition. The hyp...
Pierre Lison
CVPR
2001
IEEE
15 years 12 months ago
Mixtures of Trees for Object Recognition
Efficient detection of objects in images is complicated by variations of object appearance due to intra-class object differences, articulation, lighting, occlusions, and aspect va...
Sergey Ioffe, David A. Forsyth
ACCV
2010
Springer
14 years 4 months ago
Multiple Viewpoint Recognition and Localization
This paper presents a novel approach for labeling objects based on multiple spatially-registered images of a scene. We argue that such a multi-view labeling approach is a better fi...
Scott Helmer, David Meger, Marius Muja, James J. L...