文献类型：期刊文献

英文题名：GPSD: generative parking spot detection using multi-clue recovery model

作者：Chen, Zhihua[1];Qiu, Jun[1];Sheng, Bin[2];Li, Ping[3];Wu, Enhua[4,5]

机构：[1]East China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai, Peoples R China;[2]Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai, Peoples R China;[3]Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China;[4]Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China;[5]Univ Macau, Fac Sci & Technol, Macau, Peoples R China

年份：2021

卷号：37

期号：9-11

起止页码：2657

外文期刊名：VISUAL COMPUTER

收录：;EI(收录号：20212610550516);WOS:【SCI-EXPANDED(收录号:WOS:000663489600003)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grants 61672228, 62077037, 61872241, 62072449 and 61632003, in part by the Shanghai Automotive Industry Science and Technology Development Foundation under Grant 1837, in part by the Science and Technology Commission of Shanghai Municipality under Grants 18410750700 and 17411952600, and in part by The Hong Kong Polytechnic University under Grants P0030419, P0030929 and P0035358.

语种：英文

外文关键词：Auto-parking; Parking spot detection; Multi-clue recovery model; Corner recognition

摘要：Due to various complex environmental factors and parking scenes, there are more stringent requirements for automatic parking than the manual one. The existing auto-parking technology is based on space or plane dimension, where the former usually ignores the ground parking spot lines which may cause parking at a wrong position, while the latter often costs a lot of time in object classification which may decreases the algorithm applicability. In this paper, we propose a Generative Parking Spot Detection algorithm which uses a multi-clue recovery model to reconstruct parking spots. In the proposed method, we firstly dismantle the parking spot geometrically for marking the location of its corresponding corners and then use a micro-target recognition network to find corners from the ground image taken by car cameras. After these, we use the multi-clue model to correct the fully pairing map so that the reliable true parking spot can be recovered correctly. The proposed algorithm is compared with several existing algorithms, and the experimental result shows that it has a higher accuracy than others which can reach more than 80% in most test cases.