Paper Info
Title
Vector Quantization Enhancement for Computer Vision Tasks.
Abstract
This paper augments the Bag-of-Word scheme in several respects: we incorporate a category label into the clustering process, build classifier-tailored codebooks, and weight codewords according to their probability to occur. A size-adaptive feature clustering algorithm is also proposed as an alternative to k-means. Experiments on the PASCAL VOC 2007 challenge validate the approach for classical hard-assignment as well as VLAD encoding.
Year
DOI
Venue
2016
10.1007/978-3-319-48680-2_35
ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2016
Field
DocType
Volume
Computer vision,Digital video,Fisher vector,Pattern recognition,Computer science,Image processing,Vector quantization,Artificial intelligence,Cluster analysis,Encoding (memory)
Conference
10016
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
20
2
Name
Order
Citations
PageRank
Rémi Trichet1277.32
Noel E. O'Connor22137223.20