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Pedestrian Orientation Estimation Using CNN and Depth Camera
Technical Paper
2020-01-0700
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
This work presents a method for estimating human body orientation using a combination of convolutional neural network (CNN) and stereo camera in real time. The approach uses the CNN model to predict certain human body keypoints then transforms these points into a 3D space using the stereo vision system to estimate the body orientations. The CNN module is trained to estimate the shoulders, the neck and the nose positions, detecting of three points is required to confirm human detection and provided enough data to translate the points into 3D space.
Citation
Abughalieh, K. and Alawneh, S., "Pedestrian Orientation Estimation Using CNN and Depth Camera," SAE Technical Paper 2020-01-0700, 2020, https://doi.org/10.4271/2020-01-0700.Data Sets - Support Documents
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References
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