{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:39Z","timestamp":1750220739444,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":11,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T00:00:00Z","timestamp":1588896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Xiamen University Tan Kah Kee College","award":["JG2019SRF06"],"award-info":[{"award-number":["JG2019SRF06"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,5,8]]},"DOI":"10.1145\/3390557.3394295","type":"proceedings-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T10:22:10Z","timestamp":1591266130000},"page":"59-63","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Development of Intelligent Human Flow Density Detection System based on Sensor Fusion"],"prefix":"10.1145","author":[{"given":"Yi-Horng","family":"Lai","sequence":"first","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Xiamen University Tan Kah Kee College, China Zhangzhou campus of Xiamen University, Longhai City, Zhangzhou, Fujian, P.R.C"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-Cheng","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jau-Woei","family":"Perng","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,6,4]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2904712"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2017.07.007"},{"key":"e_1_3_2_1_3_1","volume-title":"Box Out: Beyond Counting Persons in Crowds. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Liu Y.a.S.","year":"2019","unstructured":"Liu , Y.a.S. , Miaojing and Zhao, Qijun and Wang, Xiaofang, Point in , Box Out: Beyond Counting Persons in Crowds. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2019 . June. Liu, Y.a.S., Miaojing and Zhao, Qijun and Wang, Xiaofang, Point in, Box Out: Beyond Counting Persons in Crowds. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. June."},{"key":"e_1_3_2_1_4_1","first-page":"2160","author":"Chan A.B.","year":"2012","unstructured":"Chan , A.B. and N. Vasconcelos , Counting People With Low-Level Features and Bayesian Regression. IEEE Transactions on Image Processing , 2012 . 21(4): 2160 -- 2177 . Chan, A.B. and N. Vasconcelos, Counting People With Low-Level Features and Bayesian Regression. IEEE Transactions on Image Processing, 2012. 21(4): 2160--2177.","journal-title":"Counting People With Low-Level Features and Bayesian Regression. IEEE Transactions on Image Processing"},{"key":"e_1_3_2_1_5_1","volume-title":"CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. IEEE\/CVF Conference on Computer Vision and Pattern Recognition.","author":"Li Y.","year":"2018","unstructured":"Li , Y. , X. Zhang , and D. Chen . CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2018 . Li, Y., X. Zhang, and D. Chen. CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2018."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAIS.2018.8570435"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2012.6232293"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353481"},{"key":"e_1_3_2_1_9_1","volume-title":"Remote Sensing","author":"Li S.","year":"2017","unstructured":"Li , S. , et al., Estimating Leaf Area Density of Individual Trees Using the Point Cloud Segmentation of Terrestrial Li DAR Data and a Voxel-Based Model . Remote Sensing , 2017 . 9(11): 1202. Li, S., et al., Estimating Leaf Area Density of Individual Trees Using the Point Cloud Segmentation of Terrestrial LiDAR Data and a Voxel-Based Model. Remote Sensing, 2017. 9(11): 1202."},{"key":"e_1_3_2_1_10_1","first-page":"2139","author":"Pusztai Z.","year":"2018","unstructured":"Pusztai , Z. , I. Eichhardt , and L. Hajder , Accurate Calibration of Multi-LiDAR-Multi-Camera Systems. Sensors , 2018 . 18(7): 2139 . Pusztai, Z., I. Eichhardt, and L. Hajder, Accurate Calibration of Multi-LiDAR-Multi-Camera Systems. Sensors, 2018. 18(7): 2139.","journal-title":"Accurate Calibration of Multi-LiDAR-Multi-Camera Systems. Sensors"},{"key":"e_1_3_2_1_11_1","volume-title":"Remote Sensing","author":"Wang W.","year":"2017","unstructured":"Wang , W. , K. Sakurada , and N. Kawaguchi , Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard . Remote Sensing , 2017 . 9(8): 851. Wang, W., K. Sakurada, and N. Kawaguchi, Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard. Remote Sensing, 2017. 9(8): 851."}],"event":{"name":"ICIAI 2020: 2020 the 4th International Conference on Innovation in Artificial Intelligence","sponsor":["The Hong Kong Polytechnic The Hong Kong Polytechnic University","Xi'an Jiaotong-Liverpool University Xi'an Jiaotong-Liverpool University"],"location":"Xiamen China","acronym":"ICIAI 2020"},"container-title":["Proceedings of the 2020 the 4th International Conference on Innovation in Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3390557.3394295","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3390557.3394295","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:36Z","timestamp":1750199916000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3390557.3394295"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,8]]},"references-count":11,"alternative-id":["10.1145\/3390557.3394295","10.1145\/3390557"],"URL":"https:\/\/doi.org\/10.1145\/3390557.3394295","relation":{},"subject":[],"published":{"date-parts":[[2020,5,8]]},"assertion":[{"value":"2020-06-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}