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» Effective Multiple Vector Quantization for Image Compression
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ICPR
2002
IEEE
15 years 10 months ago
Comparative Study on Mirror Image Learning (MIL) and GLVQ
In this paper the effectiveness of a corrective learning algorithm MIL (Mirror Image Learning) [1], [2] is comparatively studied with that of GLVQ (Generalized Learning Vector Qua...
Meng Shi, Tetsushi Wakabayashi, Wataru Ohyama, Fum...
105
Voted
CGF
2008
156views more  CGF 2008»
14 years 9 months ago
Render2MPEG: A Perception-based Framework Towards Integrating Rendering and Video Compression
Currently 3D animation rendering and video compression are completely independent processes even if rendered frames are streamed on-the-fly within a client-server platform. In suc...
Robert Herzog, Shin-ichi Kinuwaki, Karol Myszkowsk...
ICCV
2005
IEEE
15 years 11 months ago
Creating Efficient Codebooks for Visual Recognition
Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and...
Bill Triggs, Frédéric Jurie
TCSV
2002
121views more  TCSV 2002»
14 years 9 months ago
Rate-constrained multihypothesis prediction for motion-compensated video compression
Abstract-- This article investigates linearly combined motion-compensated signals for video compression. In particular, we discuss multiple motion-compensated signals that are join...
Markus Flierl, Thomas Wiegand, Bernd Girod
ICPR
2008
IEEE
15 years 10 months ago
A machine learning based scheme for double JPEG compression detection
Double JPEG compression detection is of significance in digital forensics. We propose an effective machine learning based scheme to distinguish between double and single JPEG comp...
Chunhua Chen, Wei Su, Yun Q. Shi