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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| Published in: | Computer vision and image understanding Vol. 141; pp. 126 - 137 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
01.12.2015
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| Subjects: | |
| ISSN: | 1077-3142, 1090-235X |
| Online Access: | Get full text |
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| Summary: | •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. |
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| ISSN: | 1077-3142 1090-235X |
| DOI: | 10.1016/j.cviu.2015.07.009 |