Human–computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

•Hand-gesture recognition system based on color imagery for HCI.•Design of a novel spatio-temporal descriptor with a high discriminative power.•Sensible combination of spatial (local and global) and temporal information.•Obtained results outperform other relevant works using depth and color imagery....

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Veröffentlicht in:Computer vision and image understanding Jg. 141; S. 126 - 137
Hauptverfasser: Maqueda, Ana I., del-Blanco, Carlos R., Jaureguizar, Fernando, García, Narciso
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Inc 01.12.2015
Schlagworte:
Classification
Hand gestures
Image descriptor
LBP
Patterns
Recognition
Segmentation
Spatio-temporal
SVM
Video descriptor
Spatio-temporal
Video descriptor
Image descriptor
Segmentation
Classification
Hand gestures
LBP
SVM
Patterns
Recognition
ISSN:1077-3142, 1090-235X
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Beschreibung
Zusammenfassung:•Hand-gesture recognition system based on color imagery for HCI.•Design of a novel spatio-temporal descriptor with a high discriminative power.•Sensible combination of spatial (local and global) and temporal information.•Obtained results outperform other relevant works using depth and color imagery. A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.
ISSN:1077-3142
1090-235X
DOI:10.1016/j.cviu.2015.07.009