Preparing and simplifying method for pedestrian object training set based on surveillance video

Zhihao Li; Qiyue Sun; Yuchen Wang; Yunxia Liu; Xuesong Gao; Yang Yang

doi:10.1117/12.2604540

5 October 2021 Preparing and simplifying method for pedestrian object training set based on surveillance video

Zhihao Li, Qiyue Sun, Yuchen Wang, Yunxia Liu, Xuesong Gao, Yang Yang

Proceedings Volume 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning; 1191119 (2021) https://doi.org/10.1117/12.2604540
Event: 2nd International Conference on Computer Vision, Image and Deep Learning, 2021, Liuzhou, China

Abstract

Object detection has a wide range of applications in daily life and industrial fields. However, the success of object detection depends on a huge amount of manually labeled data. In this paper, based on the YOLO object detection model, two types of pedestrians are identified. After data enhancement and training, the performance of the model is analyzed. This paper also studies the simplification method for the training set, through the down-sampling method, continuously reduces the number of the training set, and finally obtains the simplification strategy when preparing the training set. This paper aims to provide a training set preparation and simplification method for object detection in a specific scene, so as to save computational cost and improve the efficiency of resource use.

Citation Download Citation

Zhihao Li, Qiyue Sun, Yuchen Wang, Yunxia Liu, Xuesong Gao, and Yang Yang "Preparing and simplifying method for pedestrian object training set based on surveillance video", Proc. SPIE 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning, 1191119 (5 October 2021); https://doi.org/10.1117/12.2604540

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KEYWORDS

Video surveillance

Video

Data modeling

Surveillance

Performance modeling

Sensors

Computer vision technology

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