Gesture recognition performance score: A new metric to evaluate gesture recognition systems

Pramod Kumar Pisharady, Martin Saerbeck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In spite of many choices available for gesture recognition algorithms, the selection of a proper algorithm for a specific application remains a difficult task. The available algorithms have different strengths and weaknesses making the matching between algorithms and applications complex. Accurate evaluation of the performance of a gesture recognition algorithm is a cumbersome task. Performance evaluation by recognition accuracy alone is not sufficient to predict its successful realworld implementation. We developed a novel Gesture Recognition Performance Score (GRPS) for ranking gesture recognition algorithms, and to predict the success of these algorithms in real-world scenarios. The GRPS is calculated by considering different attributes of the algorithm, the evaluation methodology adopted, and the quality of dataset used for testing. The GRPS calculation is illustrated and applied on a set of vision based hand/ arm gesture recognition algorithms reported in the last 15 years. Based on GRPS a ranking of hand gesture recognition algorithms is provided. The paper also presents an evaluation metric namely Gesture Dataset Score (GDS) to quantify the quality of gesture databases. The GRPS calculator and results are made publicly available (

Original languageEnglish (US)
Title of host publicationComputer Vision - ACCV 2014 Workshops - Revised Selected Papers
EditorsC.V. Jawahar, Shiguang Shan
PublisherSpringer Verlag
Number of pages17
ISBN (Print)9783319166278
StatePublished - 2015
Event12th Asian Conference on Computer Vision, ACCV 2014 - Singapore, Singapore
Duration: Nov 1 2014Nov 2 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th Asian Conference on Computer Vision, ACCV 2014

Bibliographical note

Publisher Copyright:
© 2015, Springer International Publishing Switzerland.


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