AFTD: a foreground target detection dataset for airport scenario

Authors: Pengchong Chen, Xiang Zhang, Wei Lin, Yonghui Huang, Chongshang Yang, Jinyang Zhang, Jianan Hou
Primary area: datasets and benchmarks
Keywords: airport surface.+video surveillance.+object detection.+movable target

Abstract:
The detection of foreground targets on airport surface is the foundation of airport  surveillance applications. However, effective algorithms and specialized benchmarks are still lacking in this area. Based on this fact, we propose an Airport Foreground Target Detection dataset (AFTD),  which contains the three most important foreground targets moving on the airport surface: aircraft, vehicle, and person.  Through self collection and collection of web images, we have obtained a total of  over 200000 images and filtered out 10050 images based on diversity principles to  form the AFTD dataset, which includes a total of 26968 aircraft instances, 24759 vehicle instances, and 5064 person instances. AFTD includes a variety of changes of these targets, such as super multi-scale, multi-level occlusion and viewangle changes, etc. In addition, we further illustrate the challenges posed by AFTD to existing algorithms through statistical analysis and detailed experiments, and discuss how to solve these challenges in the airport surveillance scenario.The AFTD dataset can be downloaded from http://www.agvs-caac.com/aftd/aftd.html.

Decision: desk reject

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