Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism
Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting f...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5763476 |
| Summary: | Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal. Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed. The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters. Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes. |
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| ISSN: | 1076-2787 1099-0526 |