2D to 3D pedestrian detection algorithm based on deep learning

Feng Wang; Weichuan Ni; Jiajun Zou; Zhiping Wan

doi:10.1117/12.3005846

10 October 2023 2D to 3D pedestrian detection algorithm based on deep learning

Feng Wang, Weichuan Ni, Jiajun Zou, Zhiping Wan

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279926 (2023) https://doi.org/10.1117/12.3005846
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Based on the actual demand of the public for 3D content generation technology and targeting the problems existing in traditional 2D to 3D image conversion methods, we propose a 2D to 3D pedestrian detection algorithm based on deep learning. The algorithm uses object segmentation to first extract the human body's 2D outline from the input image. It then combines shallow features of the image to use a fully connected layer to map latent vectors to low-dimensional mesh vertex feature vectors, ultimately generating a triangle mesh for the 3D model. By alternately using SpiralConv and upsampling operations, the 3D mesh of the pedestrian can be generated more accurately. Experimental results show that the algorithm can accurately construct a 3D model of a pedestrian and has real-time feedback capability. The algorithm is suitable for real-time monitoring scenarios such as action recognition. Compared to traditional 2D to 3D image conversion methods, the algorithm uses deep learning to automatically learn features, which has higher accuracy and transferability. Additionally, the algorithm extracts 2D contour information of the human body using object segmentation, which improves the accuracy of generating 3D meshes. We believe that this algorithm has an important role to play in the development of 3D content generation technology.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Feng Wang, Weichuan Ni, Jiajun Zou, and Zhiping Wan "2D to 3D pedestrian detection algorithm based on deep learning", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279926 (10 October 2023); https://doi.org/10.1117/12.3005846

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KEYWORDS

Detection and tracking algorithms

3D modeling

Image segmentation

3D image processing

Deep learning

Action recognition

Image processing algorithms and systems

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