NDLI: Vision-based hand grasping posture recognition in drinking activity

Content Provider	IEEE Xplore Digital Library
Author	Chua, Jia-Luen Chang, Yoong Choon Jaward, Mohamed Hisham Parkkinen, Jussi Wong, Kok-Sheik
Copyright Year	2014
Description	Author affiliation: Faculty of Comp. Sci. and Info. Tech., University of Malaya, Malaysia (Wong, Kok-Sheik) \|\| Faculty of Engineering, Multimedia University, Malaysia (Chua, Jia-Luen; Chang, Yoong Choon) \|\| School of Engineering, Monash University Malaysia, Malaysia (Jaward, Mohamed Hisham; Parkkinen, Jussi)
Abstract	Drinking activity recognition is not a well-researched area in the human activity recognition area. In this paper, a novel technique to recognize the hand grasping posture in drinking activities is proposed. The proposed method aims to overcome the accuracy issue of Kinect in detecting the correct hand position during drinking activities and no training is required to recognize the grasping posture. Instead, the proposed technique directly extracts the unique features of the grasp posture by using a special Haar-like feature on the input image. By comparing the difference between the total pixel values of each region to a set of thresholds, the grasping posture of the hand can be detected and distinguished from other non-grasping postures or non-hand images. Experimental results indicate that the proposed technique is able to achieve a relatively high accuracy (88% true positive rate and 20% false positive rate) in detecting and recognizing the normal hand grasping posture, which mainly appears in drinking activities where someone is holding a cup.
Starting Page	185
Ending Page	190
File Size	932308
Page Count	6
File Format	PDF
ISBN	9781479961207
DOI	10.1109/ISPACS.2014.7024449
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-01
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Grasping Feature extraction Educational institutions Hidden Markov models Computer vision Cameras Three-dimensional displays computer vision hand grasping posture Haar-like feature
Content Type	Text
Resource Type	Article

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