Finding a rush-out human employing a human body direction detector

Yuta Ono; Joo Kooi Tan; Akitoshi Sato

doi:10.1117/12.2521597

22 March 2019 Finding a rush-out human employing a human body direction detector

Yuta Ono, Joo Kooi Tan, Akitoshi Sato

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110491C (2019) https://doi.org/10.1117/12.2521597
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

Recently, along with rapid development of the image processing technology, image processing has been adopted in various fields for various purposes. Development of an intelligent machine that mounts a camera as an eye is a thriving technology, and it is employed not only in industrial fields but also in the fields involving ordinary citizens. Especially, development of Intelligent Transportation Systems is very active and many methods of detecting human and automobiles have been proposed using laser radars, LIDARs or in-vehicle cameras. However, they remain only on the detection of the presence of such objects and the methods to detect rush-out objects into a road have not been developed yet. In this paper, a method is proposed which detects a human from an image with his/her body direction information. This intends to detect a human who might rush out into a road in front of an ego-car. In order that the human model used for extracting the feature may capture the appearance of human rush-out properly, directional human models and classifiers are introduced. The proposed method was examined its performance experimentally and the effectiveness of the method was shown/ satisfactory results were obtained.

Citation Download Citation

Yuta Ono, Joo Kooi Tan, and Akitoshi Sato "Finding a rush-out human employing a human body direction detector", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110491C (22 March 2019); https://doi.org/10.1117/12.2521597

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KEYWORDS

Video

Sensors

Feature extraction

Cameras

Image processing

Image classification

Eye

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