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» Learning to localize detected objects
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CVPR
2006
IEEE
16 years 6 months ago
Putting Objects in Perspective
Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. In this paper, we provide a framework for p...
Derek Hoiem, Alexei A. Efros, Martial Hebert
ICPR
2004
IEEE
16 years 5 months ago
Robust Local Max-Min Filters by Normalized Power-Weighted Filtering
A normalized, power-weighted averaging filter (NPF) is a very good approximation to the well-know local maximum and minimum filters along the object edges and offers noise reducti...
Lucas J. van Vliet
WACV
2005
IEEE
15 years 10 months ago
Incorporating Background Invariance into Feature-Based Object Recognition
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
Andrew N. Stein, Martial Hebert
162
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CVPR
2010
IEEE
15 years 10 months ago
Many-to-one Contour Matching for Describing and Discriminating Object Shape
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Praveen Srinivasan, Qihui Zhu, Jianbo Shi
ICVS
2003
Springer
15 years 9 months ago
A Software Architecture for Distributed Visual Tracking in a Global Vision Localization System
The paper considers detecting and tracking multiple moving objects in real time by a multiagent active vision system. The main objective of the envisioned system is to maintain an ...
Sinisa Segvic, Slobodan Ribaric