A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera
Tracking detailed hand motion is a fundamental research topic in the area of human-computer interaction (HCI) and has been widely studied for decades. Existing solutions with single-model inputs either require tedious calibration, are expensive or lack sufficient robustness and accuracy due to occlu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/21/4680 |
| _version_ | 1798039723803934720 |
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| author | Linjun Jiang Hailun Xia Caili Guo |
| author_facet | Linjun Jiang Hailun Xia Caili Guo |
| author_sort | Linjun Jiang |
| collection | DOAJ |
| description | Tracking detailed hand motion is a fundamental research topic in the area of human-computer interaction (HCI) and has been widely studied for decades. Existing solutions with single-model inputs either require tedious calibration, are expensive or lack sufficient robustness and accuracy due to occlusions. In this study, we present a real-time system to reconstruct the exact hand motion by iteratively fitting a triangular mesh model to the absolute measurement of hand from a depth camera under the robust restriction of a simple data glove. We redefine and simplify the function of the data glove to lighten its limitations, i.e., tedious calibration, cumbersome equipment, and hampering movement and keep our system lightweight. For accurate hand tracking, we introduce a new set of degrees of freedom (DoFs), a shape adjustment term for personalizing the triangular mesh model, and an adaptive collision term to prevent self-intersection. For efficiency, we extract a strong pose-space prior to the data glove to narrow the pose searching space. We also present a simplified approach for computing tracking correspondences without the loss of accuracy to reduce computation cost. Quantitative experiments show the comparable or increased accuracy of our system over the state-of-the-art with about 40% improvement in robustness. Besides, our system runs independent of Graphic Processing Unit (GPU) and reaches 40 frames per second (FPS) at about 25% Central Processing Unit (CPU) usage. |
| first_indexed | 2024-04-11T21:57:41Z |
| format | Article |
| id | doaj.art-95c3c4da44eb4c00990bf6c339711043 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:57:41Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-95c3c4da44eb4c00990bf6c3397110432022-12-22T04:01:02ZengMDPI AGSensors1424-82202019-10-011921468010.3390/s19214680s19214680A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth CameraLinjun Jiang0Hailun Xia1Caili Guo2Beijing Key Laboratory of Network System Architecture and Convergence, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Laboratory of Network System Architecture and Convergence, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaTracking detailed hand motion is a fundamental research topic in the area of human-computer interaction (HCI) and has been widely studied for decades. Existing solutions with single-model inputs either require tedious calibration, are expensive or lack sufficient robustness and accuracy due to occlusions. In this study, we present a real-time system to reconstruct the exact hand motion by iteratively fitting a triangular mesh model to the absolute measurement of hand from a depth camera under the robust restriction of a simple data glove. We redefine and simplify the function of the data glove to lighten its limitations, i.e., tedious calibration, cumbersome equipment, and hampering movement and keep our system lightweight. For accurate hand tracking, we introduce a new set of degrees of freedom (DoFs), a shape adjustment term for personalizing the triangular mesh model, and an adaptive collision term to prevent self-intersection. For efficiency, we extract a strong pose-space prior to the data glove to narrow the pose searching space. We also present a simplified approach for computing tracking correspondences without the loss of accuracy to reduce computation cost. Quantitative experiments show the comparable or increased accuracy of our system over the state-of-the-art with about 40% improvement in robustness. Besides, our system runs independent of Graphic Processing Unit (GPU) and reaches 40 frames per second (FPS) at about 25% Central Processing Unit (CPU) usage.https://www.mdpi.com/1424-8220/19/21/4680articulated hand trackingmulti-modeldata glovedepth cameramodel-fittingreal-time |
| spellingShingle | Linjun Jiang Hailun Xia Caili Guo A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera Sensors articulated hand tracking multi-model data glove depth camera model-fitting real-time |
| title | A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera |
| title_full | A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera |
| title_fullStr | A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera |
| title_full_unstemmed | A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera |
| title_short | A Model-Based System for Real-Time Articulated Hand Tracking Using a Simple Data Glove and a Depth Camera |
| title_sort | model based system for real time articulated hand tracking using a simple data glove and a depth camera |
| topic | articulated hand tracking multi-model data glove depth camera model-fitting real-time |
| url | https://www.mdpi.com/1424-8220/19/21/4680 |
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