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» Probabilistic Location Recognition using Reduced Feature Set
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ICCV
2009
IEEE
16 years 2 months ago
FLoSS: Facility Location for Subspace Segmentation
Subspace segmentation is the task of segmenting data lying on multiple linear subspaces. Its applications in computer vision include motion segmentation in video, structure-from...
Nevena Lazic, Inmar Givoni, Brendan Frey
CJ
2002
67views more  CJ 2002»
14 years 9 months ago
Using Bloom Filters to Speed-up Name Lookup in Distributed Systems
Bloom filters make use of a "probabilistic" hash-coding method to reduce the amount of space required to store a hash set. A Bloom filter offers a trade-off between its ...
Mark C. Little, Santosh K. Shrivastava, Neil A. Sp...
ICIP
2004
IEEE
15 years 11 months ago
A probabilistic framework for object recognition in video
We propose a solution to the problem of object recognition given a continuous video sequence containing multiple views of an object. Initially, object models are acquired from ima...
Omar Javed, Mubarak Shah, Dorin Comaniciu
CVPR
1996
IEEE
15 years 1 months ago
Connectionist networks for feature indexing and object recognition
Feature indexing techniques are promising for object recognition since they can quickly reduce the set of possible matches for a set of image features. This work exploits another ...
Clark F. Olson
ICPR
2002
IEEE
15 years 10 months ago
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Berk Gökberk, Ethem Alpaydin, Lale Akarun