Region-of-interest segmentation based on Bayesian theorem for H.264 video transcoding

Author

Huang, Shu-Fen ; Chen, Mei-Juan ; Li, Mian-Shiuan

Author_Institution

Dept. of Electr. Eng., Nat. Dong-Hwa Univ., Hualien, Taiwan

fYear

2011

fDate

6-9 Nov. 2011

Firstpage

1

Lastpage

4

Abstract

This paper presents a region-of-interest (ROI) segmentation technique to facilitate the video transcoding. In the low bit-rate transmission, ROI video coding can maintain better visual quality based on the properties of the human visual system (HVS). In this paper, to aim this purpose, the Bayesian theorem is utilized to automatically determine the moving foreground objects by using motion intensity analysis and skin color information for inter coded frames. Experimental results show that the proposed method can extract ROI macroblocks (MBs) effectively.

Keywords

Bayes methods; feature extraction; image colour analysis; image motion analysis; image segmentation; video coding; Bayesian theorem; H.264 video transcoding; ROI macroblocks extraction; ROI video coding; human visual system; inter coded frames; low bit-rate transmission; motion intensity analysis; moving foreground object determination; region-of-interest segmentation; skin color information; Bayesian methods; Image color analysis; Motion segmentation; Skin; Streaming media; Transcoding; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Visual Communications and Image Processing (VCIP), 2011 IEEE

Conference_Location

Tainan

Print_ISBN

978-1-4577-1321-7

Electronic_ISBN

978-1-4577-1320-0

Type

conf

DOI

10.1109/VCIP.2011.6116002

Filename

6116002