Moving skin and shadow region analysis via adaptive models

Authors:
Hsu-Yung Cheng;Chih-Chang Yu
Affiliations:
National Central University, Jhongli City, Taoyuan, Taiwan;Vanung University, Chung-Li, Tao-Yuan, Taiwan
Venue:
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Year:
2013

Citing 5
Cited 0

Skin Segmentation Using Color Pixel Classification: Analysis and Comparison

IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Removing Cast Shadows through a Multidistribution Approach

IEEE Transactions on Pattern Analysis and Machine Intelligence
ShadowPlay: a generative model for nonverbal human-robot interaction

Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
Detecting skin in face recognition systems: A colour spaces study

Digital Signal Processing
A Novel Approach to Analyzing Object Motion Behavior

IIH-MSP '12 Proceedings of the 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work, moving skin and shadow regions are analyzed and detected using adaptive mixture models. Both motion information and clues from skin and shadow properties are used to construct and update the models. The skin and shadow probabilities of each pixel are integrated into the mixture model framework. Furthermore, the adaptive mixtures are updated dynamically with learning rates adjusted by the skin and shadow probabilities. The experimental results have validated the effectiveness of the proposed method.