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ICRA
2006
IEEE
177views Robotics» more  ICRA 2006»
13 years 11 months ago
Autonomous Shape Model Learning for Object Localization and Recognition
— Mobile robots do not adequately represent the objects in their environment; this weakness hinders a robot’s ability to utilize past experience. In this paper, we describe a s...
Joseph Modayil, Benjamin Kuipers
CVPR
2009
IEEE
14 years 11 months ago
Learning Mixed Templates for Object Recognition
This article proposes a method for learning object templates composed of local sketches and local textures, and investigates the relative importance of the sketches and textures ...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...
TNN
2008
178views more  TNN 2008»
13 years 4 months ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
BMVC
1998
13 years 6 months ago
ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
Norbert Krüger, Niklas Lüdtke
CVPR
2001
IEEE
14 years 6 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb