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IDFusion: Joint Angle Measurement Method through Fusion of Inertial Measurement Sensor and Depth Camera
Juyeon Park, Mingyu Park, Gyumin Park, Hyun Lee
http://doi.org/10.5626/JOK.2025.52.3.208
Recent advancements in human and object recognition technologies are increasingly applied across various fields, particularly in motion detection research utilizing inertial measurement sensors and depth cameras in areas such as gaming, healthcare, and security. However, challenges such as cumulative errors and variable measurement accuracies depending on the environment persist. This study proposed IDFusion, a method that could integrate inertial measurement sensors and depth cameras for joint angle measurement, distinguishing itself through data transformation and joint angle conversion stages before fusion. Comparative analysis against using inertial measurement sensors and depth cameras individually demonstrated a superior performance of IDFusion. This technique holds promise for applications in healthcare, sports science, and human-computer interaction.
A Recognition of Violence Using Mobile Sensor Fusion in Intelligent Video Surveillance Systems
HyunIn Cha, KwangHo Song, Yoo-Sung Kim
http://doi.org/10.5626/JOK.2018.45.6.533
In this paper, we propose a violence recognition model by reflecting features extracted by concurrent and continuous action in intelligent CCTV through detecting group ROI(Region of Interest) from image. And then, proposed model uses extracted motion information obtained by using Dense Optical Flow algorithm in ROI and fusing of the acceleration and angular velocity information obtained from the inertial measurement unit of the mobile device possessed by actor. Experiments were performed to evaluate the reduction of the computation time of the proposed model and improvement of the performance degradation due to the occlusion. Result of experiment, the execution time was about 51 times faster and the accuracy of recognition of violence was improved by 11% compared to previous research methods. Therefore, the proposed model can overcome the problem of real-time failure due to excessive computation and can solve the problem of invisibility due to occlusion by actor in the image in recognition of violence.
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