{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T11:26:10Z","timestamp":1722943570085},"reference-count":30,"publisher":"Engineering and Technology Publishing","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["jcm"],"published-print":{"date-parts":[[2017]]},"DOI":"10.12720\/jcm.12.11.617-622","type":"journal-article","created":{"date-parts":[[2018,9,14]],"date-time":"2018-09-14T05:50:26Z","timestamp":1536904226000},"page":"617-622","source":"Crossref","is-referenced-by-count":0,"title":["A Method for People Counting Using Low-level Features Based on SVR with PSO Optimization"],"prefix":"10.12720","author":[{"name":"Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing and 100101, China","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaojiao","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haitao","family":"Lou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4977","published-online":{"date-parts":[[2017]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/cvpr.2007.382977","article-title":"A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis","volume-title":"Proc IEEE Conference on Computer Vision & Pattern Recognition","author":"Ali","year":"2007","unstructured":"[1] S. Ali and M. Shah, \"A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis,\" in Proc. IEEE Conference on Computer Vision & Pattern Recognition, 2007, pp.1-6."},{"key":"ref1","first-page":"90","article-title":"Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors","volume-title":"Proc Tenth IEEE International Conference on Computer Vision IEEE Computer Society","author":"Wu","year":"2005","unstructured":"[2] B. Wu and R. Nevatia, \"Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors,\" in Proc. Tenth IEEE International Conference on Computer Vision IEEE Computer Society, 2005, pp. 90-97."},{"issue":"no. 6","key":"ref2","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/3468.983420","article-title":"Estimation of number of people in crowded scenes using perspective transformation","volume":"31","author":"Lin","year":"2001","unstructured":"[3] S. Lin, J. Chen, and H. Chao, \"Estimation of number of people in crowded scenes using perspective transformation,\" IEEE Transactions Systems Man, and Cybernetics-Part A Systems and Humans, vol. 31, no. 6, pp. 645\u2013654, 2001.","journal-title":"IEEE Trans Syst Man Cybern A Syst Hum","ISSN":"http:\/\/id.crossref.org\/issn\/1083-4427","issn-type":"print"},{"key":"ref3","first-page":"31","article-title":"Video analysis using corner motion statistics","volume-title":"Proc IEEE Int Workshop on Performance Evaluation of Tracking & Surveillance","author":"Albiol","year":"2009","unstructured":"[4] A. Albiol, M. J. Silla, A. Albiol, and J. M. Mossi, \"Video analysis using corner motion statistics,\" in Proc. IEEE Int. Workshop on Performance Evaluation of Tracking & Surveillance, 2009, pp. 31\u201338."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1109\/mmsp.2013.6659261","article-title":"Crowd density map estimation based on feature tracks","volume-title":"Proc International Workshop on Multimedia Signal Processing","author":"Fradi","year":"2013","unstructured":"[5] H. Fradi and J. L. Dugelay, \"Crowd density map estimation based on feature tracks,\" in Proc. International Workshop on Multimedia Signal Processing, 2013, pp. 40-45."},{"key":"ref5","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1109\/wifs.2012.6412657","article-title":"Low level crowd analysis using frame-wise normalized feature for people counting","volume-title":"Proc IEEE International Workshop on Information Forensics and Security","author":"Fradi","year":"2012","unstructured":"[6] H. Fradi and J. L. Dugelay, \"Low level crowd analysis using frame-wise normalized feature for people counting,\" in Proc. IEEE International Workshop on Information Forensics and Security, 2012, pp.246-251."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1109\/avss.2010.78","article-title":"A Method for Counting People in Crowded Scenes","volume-title":"Proc IEEE International Conference on Advanced Video & Signal Based Surveillance IEEE Computer Society","author":"Conte","year":"2010","unstructured":"[7] D. Conte, et al., \"A Method for Counting People in Crowded Scenes,\" in Proc. IEEE International Conference on Advanced Video & Signal Based Surveillance IEEE Computer Society, 2010, pp. 225-232."},{"issue":"no. 2","key":"ref7","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1023\/A:1026226617974","article-title":"A people-counting system using a hybrid RBF neural network","volume":"18","author":"Huang","year":"2003","unstructured":"[8] D. Huang and T. W. S. Chow, \"A people-counting system using a hybrid RBF neural network,\" Neural Processing Letters, vol. 18, no. 2, pp. 97-113, 2003.","journal-title":"Neural Process Lett","ISSN":"http:\/\/id.crossref.org\/issn\/1370-4621","issn-type":"print"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"2467","DOI":"10.1109\/cvpr.2013.319","article-title":"Cumulative attribute space for age and crowd density estimation","volume-title":"Proc IEEE Conference on Computer Vision and Pattern Recognition IEEE Computer Society","author":"Chen","year":"2013","unstructured":"[9] K. Chen, et al., \"Cumulative attribute space for age and crowd density estimation,\" in Proc. IEEE Conference on Computer Vision and Pattern Recognition IEEE Computer Society, 2013, pp. 2467-2474."},{"key":"ref9","first-page":"2685","volume-title":"Learning to count with regression forest and structured labels","author":"Fiaschi","year":"2012","unstructured":"[10] L. Fiaschi, et al., \"Learning to count with regression forest and structured labels,\" pp. 2685-2688, 2012."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"2219","DOI":"10.1109\/cvpr.2014.284","article-title":"L0 regularized stationary time estimation for crowd group analysis","volume-title":"Proc IEEE Conference on Computer Vision and Pattern Recognition","author":"Yi","year":"2014","unstructured":"[11] S. Yi, et al., \"L0 regularized stationary time estimation for crowd group analysis,\" in Proc. IEEE Conference on Computer Vision and Pattern Recognition, 2014, pp. 2219- 2226."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/icmew.2012.71","article-title":"Crowd density estimation based on local binary pattern co-occurrence matrix","volume-title":"Proc IEEE International Conference on Multimedia and Expo Workshops","author":"Wang","year":"2012","unstructured":"[12] Z. Wang, et al., \"Crowd density estimation based on local binary pattern co-occurrence matrix,\" in Proc. IEEE International Conference on Multimedia and Expo Workshops, 2012, pp. 372-377."},{"key":"ref12","first-page":"1","article-title":"Estimating the number of people in crowded scenes by MID based foreground segmentation and headshoulder detection","volume-title":"Proc International Conference on Pattern Recognition","author":"Li","year":"2008","unstructured":"[13] M. Li, et al., \"Estimating the number of people in crowded scenes by MID based foreground segmentation and headshoulder detection,\" in Proc. International Conference on Pattern Recognition, 2008, pp. 1-4."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"2423","DOI":"10.1109\/iccv.2011.6126526","article-title":"Density-aware person detection and tracking in crowds","volume-title":"Proc IEEE International Conference on Computer Vision","author":"Rodriguez","year":"2011","unstructured":"[14] M. Rodriguez, et al., \"Density-aware person detection and tracking in crowds,\" in Proc. IEEE International Conference on Computer Vision, 2011, pp. 2423-2430."},{"issue":"no. 4","key":"ref14","doi-asserted-by":"publisher","first-page":"331","DOI":"10.4304\/jmm.8.4.331-337","article-title":"Crowd density estimation based on texture feature extraction","volume":"8","author":"Wang","year":"2013","unstructured":"[15] B. Wang, et al., \"Crowd density estimation based on texture feature extraction,\" Journal of Multimedia, vol. 8, no. 4, pp. 331-337, 2013.","journal-title":"J Multimed","ISSN":"http:\/\/id.crossref.org\/issn\/1796-2048","issn-type":"print"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"2622","DOI":"10.1109\/cvpr.2010.5539975","article-title":"Multi-task warped Gaussian process for personalized age estimation","volume-title":"Proc IEEE Conference on Computer Vision & Pattern Recognition","author":"Zhang","year":"2010","unstructured":"[16] Y. Zhang and D. Y. Yeung, \"Multi-task warped Gaussian process for personalized age estimation,\" in Proc. IEEE Conference on Computer Vision & Pattern Recognition, pp. 2622-2629, 2010."},{"key":"ref16","first-page":"1591","article-title":"Learning to count objects in images","volume-title":"Proc Conference on Neural Information Processing Systems","author":"Lempitsky","year":"2010","unstructured":"[17] V. Lempitsky, S. Victor, and A. Zisserman. \"Learning to count objects in images,\" in Proc. Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, 2010, pp. 1591-1591."},{"key":"ref17","first-page":"2256","article-title":"From semi-supervised to transfer counting of crowds","volume-title":"Proc IEEE International Conference on Computer Vision","author":"Chen","year":"2013","unstructured":"[18] C. L. Chen, S. Gong, et al., \"From semi-supervised to transfer counting of crowds,\" in Proc. IEEE International Conference on Computer Vision, 2013, pp. 2256-2263."},{"issue":"no. 1","key":"ref18","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1049\/ecej:19950106","article-title":"Crowd monitoring using image processing","volume":"7","author":"Davies","year":"1995","unstructured":"[19] A. C. Davies, J. H. Yin, et al., \"Crowd monitoring using image processing,\" Electronics & Communication Engineering Journal, vol. 7, no. 1, pp. 37-47, 1995.","journal-title":"Electron Commun Eng J","ISSN":"http:\/\/id.crossref.org\/issn\/0954-0695","issn-type":"print"},{"key":"ref19","first-page":"430","article-title":"Machine learning for highspeed corner detection","volume-title":"Proc 9th European Conference on Computer Vision","author":"Rosten","year":"2006","unstructured":"[20] E. Rosten and T. Drummond, \"Machine learning for highspeed corner detection,\" in Proc. 9th European Conference on Computer Vision, 2006, pp. 430-443."},{"issue":"no. 6","key":"ref20","doi-asserted-by":"publisher","first-page":"520","DOI":"10.7763\/IJMLC.2013.V3.373","article-title":"Method for estimation of crowd density using neural network with PSO optimization based on gray level co-occurrence matrix","volume":"3","author":"Xie","year":"2013","unstructured":"[21] L. Xie and P. Wang, \"Method for estimation of crowd density using neural network with PSO optimization based on gray level co-occurrence matrix,\" International Journal of Machine Learning & Computing, vol. 3, no. 6, pp. 520-523, 2013.","journal-title":"International Journal of Machine Learning & Computing"},{"key":"ref21","doi-asserted-by":"crossref","unstructured":"22. O. Meynberg and G. Kuschk, \"Airborne crowd density estimation,\" in Proc. Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. II-3\/W, 2013, pp. 49-54.","DOI":"10.5194\/isprsannals-II-3-W3-49-2013"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/iccvw.2011.6130237","article-title":"Integrating pedestrian simulation, tracking and event detection for crowd analysis","volume-title":"Proc IEEE Workshop on Modeling Simulation and Visual Analysis of Large Crowds","author":"Butenuth","year":"2011","unstructured":"[23] M. Butenuth, et al., \"Integrating pedestrian simulation, tracking and event detection for crowd analysis,\" in Proc. IEEE Workshop on Modeling, Simulation and Visual Analysis of Large Crowds, 2011, pp. 150-157."},{"issue":"no. 3","key":"ref23","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1023\/B:VISI.0000045324.43199.43","article-title":"Lucas\/Kanade Meets Horn\/Schunck: Combining local and global optic flow methods","volume":"61","author":"Bruhn","year":"2005","unstructured":"[24] A. Bruhn, J. Weickert, and C. Schn\u00f6rr, \"Lucas\/Kanade Meets Horn\/Schunck: Combining local and global optic flow methods,\" International Journal of Computer Vision, vol. 61, no. 3, pp. 211-231, 2005.","journal-title":"Int J Comput Vis","ISSN":"http:\/\/id.crossref.org\/issn\/0920-5691","issn-type":"print"},{"issue":"no. 5","key":"ref24","article-title":"Crowd density estimation based on improved harris & optics algorithm","volume":"9","author":"Cheng","year":"2014","unstructured":"[25] X. Cheng, et al., \"Crowd density estimation based on improved harris & optics algorithm,\" Journal of Computers, vol. 9, no. 5, 2014.","journal-title":"J Comput (Taipei)","ISSN":"http:\/\/id.crossref.org\/issn\/1991-1599","issn-type":"print"},{"issue":"no. 1","key":"ref25","first-page":"25","article-title":"Fully convolutional neural networks for crowd segmentation","volume":"49","author":"Kang","year":"2014","unstructured":"[26] K. Kang and X. Wang \"Fully convolutional neural networks for crowd segmentation,\" Computer Science, vol. 49, no. 1, pp. 25-30, 2014.","journal-title":"Comput Sci","ISSN":"http:\/\/id.crossref.org\/issn\/1508-2806","issn-type":"print"},{"key":"ref26","volume-title":"ViBe","author":"Barnich","year":"2011","unstructured":"[27] O. Barnich and M. Van Droogenbroeck, \"ViBe: A universal background subtraction algorithm for video sequences,\" IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, vol. 20, no. 6, pp. 1709-24, 2011."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/icassp.2009.4959741","article-title":"ViBE: A powerful random technique to estimate the background in video sequences","volume-title":"Proc IEEE International Conference on Acoustics IEEE","author":"Barnich","year":"2009","unstructured":"[28] O. Barnich and M. V. Droogenbroeck, \"ViBE: A powerful random technique to estimate the background in video sequences,\" in Proc. IEEE International Conference on Acoustics IEEE, 2009, pp. 945-948."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2008.4587569","article-title":"Privacy preserving crowd monitoring: Counting people without people models or tracking","author":"Chan","year":"2008","unstructured":"[29] A. B. Chan, Z. S. J. Liang, and N. Vasconcelos, \"Privacy preserving crowd monitoring: Counting people without people models or tracking,\" in Proc. IEEE Conf. Comput. Vis. Pattern Recog, 2008, pp. 1\u20137."},{"key":"ref29","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1109\/icnc.2009.257","article-title":"Optimization of SVM parameters based on PSO algorithm","volume-title":"Proc International Conference on Natural Computation","volume":"6","author":"Zhang","unstructured":"[30] X. Zhang and Y. Guo, \"Optimization of SVM parameters based on PSO algorithm,\" in Proc. International Conference on Natural Computation, Tianjian, China, August 14-16, 2009, vol. 6, pp. 536-539."}],"container-title":["Journal of Communications"],"original-title":[],"link":[{"URL":"http:\/\/www.jocm.us\/uploadfile\/2017\/1124\/20171124042359750.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,24]],"date-time":"2019-10-24T02:22:01Z","timestamp":1571883721000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.jocm.us\/index.php?m=content&c=index&a=show&catid=183&id=1158"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":30,"URL":"https:\/\/doi.org\/10.12720\/jcm.12.11.617-622","relation":{},"ISSN":["1796-2021"],"issn-type":[{"type":"print","value":"1796-2021"}],"subject":[],"published":{"date-parts":[[2017]]}}}