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» Structured Learning and Prediction in Computer Vision
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DAGM
2007
Springer
14 years 1 days ago
How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye Movements
Interest point detection in still images is a well-studied topic in computer vision. In the spatiotemporal domain, however, it is still unclear which features indicate useful inter...
Wolf Kienzle, Bernhard Schölkopf, Felix A. Wi...
ECCV
2002
Springer
14 years 10 months ago
Assorted Pixels: Multi-sampled Imaging with Structural Models
Abstract. Multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightn...
Shree K. Nayar, Srinivasa G. Narasimhan
IROS
2008
IEEE
135views Robotics» more  IROS 2008»
14 years 2 months ago
Interactive learning of visual topological navigation
— We present a topological navigation system that is able to visually recognize the different rooms of an apartment and guide a robot between them. Specifically tailored for sma...
David Filliat
ICCV
2009
IEEE
15 years 1 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICPR
2010
IEEE
14 years 1 months ago
On-Line Random Naive Bayes for Tracking
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...