Paper Info
Title
Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning
Abstract
Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the skin segmentation problem for gesture recognition. Initially, given a gesture video sequence, a generic skin model is applied to the first couple of frames to automatically collect the training data. Then, an SVM classifier based on active learning is used to identify the skin pixels. Finally, the results are improved by incorporating region segmentation. The proposed algorithm is fully automatic and adaptive to different signers. We have tested our approach on the ECHO database. Comparing with other existing algorithms, our method could achieve better performance
Year
DOI
Venue
2006
10.1109/FGR.2006.27
FG
Keywords
Field
DocType
gesture recognition combining region,echo database,skin segmentation,generic skin model,learning (artificial intelligence),image segmentation,region segmentation,skin segmentation problem,svm classifier,active learning,gesture video sequence,support vector machine,automatic skin segmentation,image sequences,skin pixel,gesture recognition,support vector machines,image colour analysis,filtering,skin,learning artificial intelligence,face detection,information retrieval,face recognition,image recognition,machine learning,image processing,training data
Computer vision,Facial recognition system,Scale-space segmentation,Pattern recognition,Gesture,Segmentation,Computer science,Support vector machine,Gesture recognition,Image segmentation,Artificial intelligence,Face detection
Conference
ISBN
Citations 
PageRank 
0-7695-2503-2
18
0.97
References 
Authors
11
4
Name
Order
Citations
PageRank
Junwei Han13501194.57
George Awad236229.64
Alistair Sutherland310114.36
Hai Wu4180.97