Improved single stage object detection method used in complex environments

Jiaqi Dong; Yangjie Wei

doi:10.1117/12.3031317

19 July 2024 Improved single stage object detection method used in complex environments

Jiaqi Dong, Yangjie Wei

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Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131811V (2024) https://doi.org/10.1117/12.3031317
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Due to complex landscape features and illumination variation in actual complex environments, the accuracy of existing object detection methods is unstable and limited, especially under a few-shot condition, which seriously affects their application in practical complex environments. Therefore, an object detection model based on the Attentive Single Shot Multibox Detector (ASSD) network is proposed combined with corner feature fusion and Soft-non-maximum suppression (Soft-NMS) in this study. First, the local and global information, extracted from the image convolutional layer features, and the structural and detailed information, provided by the corner features, are fused together to enrich the model’s understanding ability for spatial information, as well as the diverse feature representation capability. Second, the Soft- NMS is introduced into the traditional NMS model to reduce the false negative rate under the condition of object occlusion. Finally, the PASCAL VOC2007 and COCO datasets are used to validate the proposed model, and the experimental results show that the mAP is 83.35% on PASCAL VOC2007, which is 1.29% higher than the baseline ASSD model, and the mAP improvements of 0.57%, 1.80%, 4.53%, 9.29%, and 24.14% within the NMS threshold of 0.5-0.9, respectively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Jiaqi Dong and Yangjie Wei "Improved single stage object detection method used in complex environments", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131811V (19 July 2024); https://doi.org/10.1117/12.3031317

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KEYWORDS

Object detection

Education and training

Detection and tracking algorithms

Feature fusion

RGB color model

Data modeling

Image fusion

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