Spatial domain analysis based on human position and movement recognition for the top-view imaging systems

Seung Jun Lee; Byeong Hak Kim; Young Hyoung Kim; Min Young Kim

doi:10.1117/12.2534909

6 September 2019 Spatial domain analysis based on human position and movement recognition for the top-view imaging systems

Seung Jun Lee, Byeong Hak Kim, Young Hyoung Kim, Min Young Kim

Author Affiliations +

Proceedings Volume 11137, Applications of Digital Image Processing XLII; 111371U (2019) https://doi.org/10.1117/12.2534909
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

Abstract

The smart home appliances are dramatically growing into a big part of the consumer electronics market and they are required to have many convenient functions for users. Therefore, many products are using top-view imaging systems for advanced technologies to recognize object positions and movement for human and machine interaction. Although the topview imaging system has already developed for many applications, not only home appliances but also closed-circuit televisions (CCTV) and unmanned aerial vehicles (UAV), it still has many drawbacks. Especially the top-view image shows asymmetrical features and radially distorted scenes around the corners like omnidirectional view images. Therefore, conventional human detection methods are struggled with the computational complexity and low accuracy to calibrate its artifacts. In this paper, we propose an efficient method to recognize spatial domain of human positions and movements based on motion vector detection using multiple feature maps on the top-view images. In the experimental results, we show efficient computation time and results of spatial domain detection qualitatively.

Conference Presentation

Citation Download Citation

Seung Jun Lee, Byeong Hak Kim, Young Hyoung Kim, and Min Young Kim "Spatial domain analysis based on human position and movement recognition for the top-view imaging systems", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111371U (6 September 2019); https://doi.org/10.1117/12.2534909

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