Automated gesture segmentation from dance sequences

2004 ◽  
Author(s):  
K. Kahol ◽  
P. Tripathi ◽  
S. Panchanathan
Keyword(s):  
Gesture Segmentation

An improved mixed gaussian-based background modelling method for fast gesture segmentation of mobile terminals

2018 ◽  
Vol 35 (3-4) ◽  
pp. 243-252 ◽  
Author(s):  
Chengfeng JIAN ◽  
Tao LU ◽  
Xiaoyu XIANG ◽  
Meiyu ZHANG
Keyword(s):  
Mobile Terminals ◽  
Background Modelling ◽  
Modelling Method ◽  
Gesture Segmentation

An Improved Otsu’s Thresholding Algorithm on Gesture Segmentation

2017 ◽  
Vol 21 (2) ◽  
pp. 247-250 ◽  
Author(s):  
Chongshan Lv ◽  
◽  
Ting Zhang ◽  
Chengyuan Liu
Keyword(s):  
Gesture Recognition ◽  
Skin Color ◽  
Color Space ◽  
Gaussian Model ◽  
Adaptive Threshold ◽  
Ycbcr Color Space ◽  
Gesture Segmentation ◽  
Rgb Color Space ◽  
Similarity Graph ◽  
Thresholding Algorithm

In gesture recognition systems, segmenting gestures from complex background is the hardest and the most critical part. Gesture segmentation is the prerequisite of following image processing, and the result of segmentation has a direct influence on the result of gesture recognition. This paper proposed an algorithm of adaptive threshold gesture segmentation based on skin color. First of all, the image should be transformed from RGB color space to YCbCr color space. After eliminating luminance component Y, similarity graph of skin color will be obtained from the Gaussian model. Then Otsu adaptive threshold algorithm is used to carry out binary processing for the similarity graph of skin color. After the segmentation of skin color regions, the morphology method is used to process binary image for determining the location of hands. Experimental results show that the detailed segmentation of skin color using the dynamic-adaptive threshold can improve noise resistance and can produce better results.

A Study of Hand Gesture Segmentation Techniques for Sign Languages

2020 ◽  
Vol 17 (4) ◽  
pp. 1764-1769
Author(s):  
S. Gobhinath ◽  
T. Vignesh ◽  
R. Pavankumar ◽  
R. Kishore ◽  
K. S. Koushik
Keyword(s):  
Sign Language ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Morphological Processing ◽  
Hand Gesture ◽  
Hand Detection ◽  
Hand Segmentation ◽  
Human Gestures ◽  
Gesture Segmentation ◽  
Physically Challenged

This paper presents about an overview on several methods of segmentation techniques for hand gesture recognition. Hand gesture recognition has evolved tremendously in the recent years because of its ability to interact with machine. Mankind tries to incorporate human gestures into modern technologies like touching movement on screen, virtual reality gaming and sign language prediction. This research aims towards employed on hand gesture recognition for sign language interpretation as a human computer interaction application. Sign Language which uses transmits the sign patterns to convey meaning by hand shapes, orientation and movements to fluently express their thoughts with other person and is normally used by the physically challenged people who cannot speak or hear. Automatic Sign Language which requires robust and accurate techniques for identifying hand signs or a sequence of produced gesture to help interpret their correct meaning. Hand segmentation algorithm where segmentation using different hand detection schemes with required morphological processing. There are many methods which can be used to acquire the respective results depending on its advantage.

A Study on Hand Gesture Segmentation Approaches

2021 ◽  
pp. 641-650
Author(s):  
Jhuma Sunuwar ◽  
Samrjeet Borah ◽  
Sweta Agarwal ◽  
Sanjoy Ghatak
Keyword(s):  
Hand Gesture ◽  
Gesture Segmentation
Sign in / Sign up

Export Citation Format

Share Document