Inter mode selection for H.264/AVC using time-efficient learning-theoretic algorithms

Authors:
Yuri Vatis;Ligang Lu;Ashish Jagmohan
Affiliations:
Institute für Informationsverarbeiting Leibniz Universität Hannover, Germany;IBM T.J. Watson Research Center, Yorktown Heights;IBM T.J. Watson Research Center, Yorktown Heights
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 4
Cited 0

Optimal Partitioning for Classification and Regression Trees

IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Classification based mode decisions for video over network

IEEE Transactions on Multimedia
Feature-Based Intra-/InterCoding Mode Selection for H.264/AVC

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this we present a novel algorithm to speed up the inter mode decision process for the H264/AVC encoding. The proposed inter mode decision scheme determines the best coding mode between P16×16 and P8×8 based on learning theoretic classification algorithms to discern between mode classes based on the evaluation of a simple set of features extracted from a motion complensated macroblock. We show that the prposed method can reduce the number of macroblocks for P8×8 mode testing by 80% on average, at the cost of only a small loss of 0.1 dB in compression performance.