Integrated Collision Detection Framework Based on Pose, Depth, and Object Estimation Using a Single RGB Camera 


Vol. 15,  No. 2, pp. 160-168, Feb.  2026
https://doi.org/10.3745/TKIPS.2026.15.2.160


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  Abstract

Ensuring worker safety in dynamic industrial environments requires collision detection systems that are fast, accurate, and cost-efficient. Conventional solutions based on LiDAR or RGB-D sensors deliver high precision but are costly, maintenance-heavy, and sensitive to environmental conditions such as poor lighting, occlusion, and reflective surfaces. To address these limitations, this study proposes a lightweight collision detection framework using only a single RGB camera. The system integrates YOLOv8 for object detection, ViTPose for human pose estimation, and Depth Anything for monocular depth estimation to reconstruct 3D positions of human joints and object centers in real time. A dedicated collision detection algorithm computes Euclidean distances between these 3D coordinates, while temporal smoothing and joint-structure-based outlier correction enhance stability and reliability. The proposed framework was validated on a custom dataset of 55 scenario videos under diverse lighting conditions, camera angles, and interaction types. Experimental results show that the system achieved an F1-score of 1.0 across all scenarios, indicating high accuracy and robustness. These findings demonstrate the potential of single RGB camera systems as practical, scalable, and cost-effective alternatives to expensive sensor-based approaches, enabling real-time collision detection for industrial safety monitoring.

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[IEEE Style]

Y. C. Kim, M. J. Hong, H. Yoo, B. S. Kim, "Integrated Collision Detection Framework Based on Pose, Depth, and Object Estimation Using a Single RGB Camera," The Transactions of the Korea Information Processing Society, vol. 15, no. 2, pp. 160-168, 2026. DOI: https://doi.org/10.3745/TKIPS.2026.15.2.160.

[ACM Style]

Ye Chan Kim, Min Ju Hong, Hosang Yoo, and Byeong Soo Kim. 2026. Integrated Collision Detection Framework Based on Pose, Depth, and Object Estimation Using a Single RGB Camera. The Transactions of the Korea Information Processing Society, 15, 2, (2026), 160-168. DOI: https://doi.org/10.3745/TKIPS.2026.15.2.160.

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