Authors:
Jiwon Jun
1
;
Hyunjeong Pak
2
and
Moongu Jeon
1
Affiliations:
1
Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea
;
2
Korea Culture Technology Institute, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, South Korea
Keyword(s):
Vehicle Detection, Object Detection, Surveillance System.
Abstract:
Since surveillance cameras are commonly installed in high places, the objects in the taken images are relatively small. Detecting small objects is a hard issue for the one-stage detector, and its performance in the surveillance system is not good. Two-stage detectors work better, but their speed is too slow to use in the real-time system. To remedy the drawbacks, we propose an efficient method, named as Fixed Scale SSD(FSSSD), which is an extension of SSD. The proposed method has three key points: high-resolution inputs to detect small objects, a lightweight Backbone to speed up, and prediction blocks to enrich features. FSSSD achieve 63.7% AP at 16.7 FPS in the UA-DETRAC test dataset. The performance is similar to two-stage detectors and faster than any other one-stage method.