Title :
A modified EM algorithm for hand gesture segmentation in RGB-D data
Author :
Zhaojie Ju ; Yuehui Wang ; Wei Zeng ; Haibin Cai ; Honghai Liu
Author_Institution :
Intell. Syst. & Biomed. Robot. Group, Univ. of Portsmouth, Portsmouth, UK
Abstract :
This paper proposes a novel method with a modified Expectation-Maximisation (EM) Algorithm to segment hand gestures in the RGB-D data captured by Kinect. With the depth map and RGB image aligned by the genetic algorithm to estimate the key points from both depth and RGB images, a novel approach is proposed to refine the edge of the tracked hand gesture, which is used to segment the RGB image of the hand gestures, by applying a modified EM algorithm based on Bayesian networks. The experimental results demonstrated the modified EM algorithm effectively adjusts the RGB edges of the segmented hand gestures. The proposed methods have potential to improve the performance of hand gesture recognition in Human-Computer Interaction (HCI).
Keywords :
belief networks; edge detection; expectation-maximisation algorithm; genetic algorithms; gesture recognition; human computer interaction; image colour analysis; image segmentation; Bayesian networks; HCI; Kinect; RGB edges; RGB image; RGB-D data; depth map; genetic algorithm; hand gesture segmentation; human-computer interaction; modified EM algorithm; modified expectation-maximisation algorithm; Calibration; Cameras; Genetic algorithms; Gesture recognition; Image edge detection; Image segmentation; Motion segmentation;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891777