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U‐FPNDet: A one‐shot traffic object detector based on U‐shaped feature pyramid module
- Source :
- IET Image Processing, Vol 15, Iss 10, Pp 2146-2156 (2021)
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- In the field of automatic driving, identifying vehicles and pedestrians is the starting point of other automatic driving techniques. Using the information collected by the camera to detect traffic targets is particularly important. The main bottleneck of traffic object detection is due to the same category of targets, which may have different scales. For example, the pixel‐level of cars may range from 30 to 300 px, which will cause instability of positioning and classification. In this paper, a multi‐dimension feature pyramid is constructed in order to solve the multi‐scale problem. The feature pyramid is built by developing a U‐shaped module and using a cascade‐method. In order to verify the effectiveness of the U‐shaped module, we also designed a new one‐shot detector U‐FPNDet. The model first extracts the basic feature map by using the basic network and constructs the multi‐dimension feature pyramid. Next, a pyramid pooling module is used to get more context information from the scene. Finally, the detection network is run on each level of the pyramid to obtain the final result by NMS. By using this method, a state‐of‐the‐art performance is achieved on both detection and classification on commonly used benchmarks.
- Subjects :
- One shot
Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
QA76.75-76.765
Feature (computer vision)
Signal Processing
Pyramid
Photography
Object detector
Computer vision
Computer Vision and Pattern Recognition
Artificial intelligence
Computer software
Electrical and Electronic Engineering
business
TR1-1050
Software
Subjects
Details
- Language :
- English
- ISSN :
- 17519659 and 17519667
- Volume :
- 15
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- IET Image Processing
- Accession number :
- edsair.doi.dedup.....e85f19b6e47b118876a8f9ca9d9692e2