SHREC 2022 track on online detection of heterogeneous gestures. (October 2022)

• Record Type: Journal Article
• Authors: Emporio, Marco; Caputo, Ariel; Giachetti, Andrea; Cristani, Marco; Borghi, Guido; D'Eusanio, Andrea; Le, Minh-Quan; Nguyen, Hai-Dang; Tran, Minh-Triet; Ambellan, Felix; Hanik, Martin; Nava-Yazdani, Esfandiar; von Tycowicz, Christoph
• Is Part Of: Computers & graphics. Volume 107(2022)
• Page Start: 241
• Page End: 251
• Publication Date: 2022-10
• Subjects: Computers and graphics -- Formatting -- Guidelines; Computer graphics -- Periodicals; 006.6
• DOI: 10.1016/j.cag.2022.07.015
• Languages: English
• ISSNs: 0097-8493

Abstract

Abstract: This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses. The task is the detection of gestures belonging to a dictionary of 16 classes characterized by different pose and motion features. The dataset features continuous sequences of hand tracking data where the gestures are interleaved with non-significant motions. The data have been captured using the Hololens 2 finger tracking system in a realistic use-case of mixed reality interaction. The evaluation is based not only on the detection performances but also on the latency and the false positives, making it possible to understand the feasibility of practical interaction tools based on the algorithms proposed. The outcomes of the contest's evaluation demonstrate the necessity of further research to reduce recognition errors, while the computational cost of the algorithms proposed is sufficiently low. Graphical abstract: Highlights: 3D Shape Retrieval Challenge 2022 at 3DOR'22 Track on Online detection of heterogeneous gestures. New gesture dataset with 288 gestures sequences and 16 gestures dictionary. Contest with 4 groups presenting their gesture recognition methods and different variants. Report of results and performances for all the methods.