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» Multiple Kernels for Object Detection
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ACCV
2007
Springer
14 years 3 months ago
Detecting and Segmenting Un-occluded Items by Actively Casting Shadows
We present a simple and practical approach for segmenting un-occluded items in a scene by actively casting shadows. By ’items’, we refer to objects (or part of objects) enclose...
Tze Ki Koh, Amit K. Agrawal, Ramesh Raskar, Steve ...
EWSN
2009
Springer
14 years 3 months ago
SCOPES: Smart Cameras Object Position Estimation System
In this paper we present SCOPES, a distributed Smart Camera Object Position Estimation sensor network System that provides maps of distribution of people in indoors environments. ...
Ankur Kamthe, Lun Jiang, Matthew Dudys, Alberto Ce...
NIPS
2003
13 years 10 months ago
Mutual Boosting for Contextual Inference
Mutual Boosting is a method aimed at incorporating contextual information to augment object detection. When multiple detectors of objects and parts are trained in parallel using A...
Michael Fink 0002, Pietro Perona
BMCBI
2006
134views more  BMCBI 2006»
13 years 9 months ago
A statistical score for assessing the quality of multiple sequence alignments
Background: Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein...
Virpi Ahola, Tero Aittokallio, Mauno Vihinen, Esa ...
ECCV
2010
Springer
13 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof