Abstract
Pedestrians “texting-while-walking” increase the risk of traffic accidents, since they are often not paying attention to their surrounding environments and fails to notice approaching vehicles. Thus, the recognition of texting-while-walking from an in-vehicle camera should be helpful for safety driving assistance. In this paper, we propose a method to recognize a pedestrian texting-while-walking from in-vehicle camera images. The proposed approach focuses on the characteristic relationship between the arm and the head poses observed during a texting-while-walking behavior. In this paper, Pose-Dependent Joint HOG feature is proposed as a novel feature, which uses parts locations as prior knowledge and describes the cooccurrence of the arm and the head poses. To show the effectiveness of the proposed method, we constructed a dataset and evaluated it.
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Acknowledgement
This research is partially supported by the Center of Innovation Program (Nagoya-COI) from Japan Science and Technology Agency and Grant-in-Aid for Scientific Research from The Ministry of Education, Culture, Sports, Science and Technology.
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Shinmura, F., Kawanishi, Y., Deguchi, D., Ide, I., Murase, H., Fujiyoshi, H. (2017). Recognition of Texting-While-Walking by Joint Features Based on Arm and Head Poses. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10116. Springer, Cham. https://doi.org/10.1007/978-3-319-54407-6_30
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DOI: https://doi.org/10.1007/978-3-319-54407-6_30
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