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» Boosting Object Detection Using Feature Selection
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ICPR
2008
IEEE
16 years 17 days ago
Contour grouping with shape manifold and distance transform
Object detection in clutter or occlusion is a hard problem in computer vision. We propose an object detection method based on contour grouping. Two stages are included: a novel di...
Zou Qi, Luo Siwei, Huang Yaping, Li Yan
153
Voted
DIS
2006
Springer
15 years 9 months ago
Automatic Recognition of Landforms on Mars Using Terrain Segmentation and Classification
Mars probes send back to Earth enormous amount of data. Automating the analysis of this data and its interpretation represents a challenging test of significant benefit to the doma...
Tomasz F. Stepinski, Soumya Ghosh, Ricardo Vilalta
MICCAI
2003
Springer
16 years 7 months ago
An Automatic System for Classification of Nuclear Sclerosis from Slit-Lamp Photographs
A robust and automatic system has been developed to detect the visual axis and extract important feature landmarks from slit-lamp photographs, and objectively grade the severity of...
Shaohua Fan, Charles R. Dyer, Larry Hubbard, Barba...
NIPS
2001
15 years 7 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
177
Voted
ICRA
2008
IEEE
204views Robotics» more  ICRA 2008»
16 years 17 days ago
Active exploration and keypoint clustering for object recognition
— Object recognition is a challenging problem for artificial systems. This is especially true for objects that are placed in cluttered and uncontrolled environments. To challenge...
Gert Kootstra, Jelmer Ypma, Bart de Boer