Hand Tracking and Gesture Recognition by Multiple Contactless Sensors: A Survey

• Type: Article in International Scientific Journal
• Date: 2022-02

Authors

Eleni Theodoridou (Author) Other; Luigi Cinque (Author) Other; Filippo Mignosi (Author) Other; Giuseppe Placidi (Author) Other; Matteo Polsinelli (Author) Other; João Manuel R. S. Tavares (Author) FEUP; Matteo Spezialetti (Author) Other

Journal

Title: IEEE Transactions on Human-Machine Systems

Vol. 53 No. 1

Pages: 35-43

ISSN: 2168-2291

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Clarivate Analytics

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00X-0MK

DOI: 10.1109/thms.2022.3188840

Abstract (EN): Hand tracking and gesture recognition are fundamental in a multitude of applications. Various sensors have been used for this purpose, however, all monocular vision systems face limitations caused by occlusions. Wearable equipment overcome said limitations, although deemed impractical in some cases. Using more than one sensor provides a way to overcome this problem, but necessitates more complicated designs. In this work, we aim to highlight contemporary methods used for hand tracking and gesture recognition by collecting publications of systems developed in the last decade, that employ contactless devices as RGB cameras, IR, and depth sensors, along with some preceding pillar works. Additionally, we briefly present common steps, techniques, and basic algorithms used during the process of developing modern hand tracking and gesture recognition systems and, finally, we derive the trend for the next future.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9