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Sensors 2017, 17(1), 166; doi:10.3390/s17010166

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
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Academic Editor: Vittorio M. N. Passaro
Received: 25 November 2016 / Revised: 10 January 2017 / Accepted: 12 January 2017 / Published: 17 January 2017
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Abstract

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity. View Full-Text
Keywords: joint filter; thermal sensor; visual sensor; hand gesture tracking; hand gesture recognition; varying lighting conditions joint filter; thermal sensor; visual sensor; hand gesture tracking; hand gesture recognition; varying lighting conditions
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, S.; Ban, Y.; Lee, S. Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter. Sensors 2017, 17, 166.

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