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Abstrakty
In this paper we present an algorithm for precise estimation of moving objects density (typically people and vehicles) in indoor and outdoor scenes. Automatic generation of the so-called density maps is based on video sequences acquired by surveillance systems. Our approach offers two types of solutions. The first one increments the accumulation table when a moving object is detected in a location of interest, delivering a density map of the presence of moving objects. The second algorithm increments the accumulation table only in cases of detecting a new moving object, resulting in a density map of the count of moving objects. The proposed algorithms were tested with the use of PETS 2009 database and with our own database of long-term video recordings. Finally, results of the density maps visualization and determination of the “busy hours” are presented.
Rocznik
Tom
Strony
119--132
Opis fizyczny
Bibliogr. 24 poz., tab., rys.
Twórcy
autor
- Faculty of Computing, Poznan University of Technology, Poznan, Poland
autor
- Faculty of Computing, Poznan University of Technology, Poznan, Poland
autor
- Faculty of Computing, Poznan University of Technology, Poznan, Poland
autor
- Faculty of Computing, Poznan University of Technology, Poznan, Poland
Bibliografia
- [1] Bosch IVA 5.60 datasheet, http://resource.boschsecurity.us/documents/DS_IVA_5_60_Data_sheet_enUS_11858668555.pdf, available at 2014-11-27
- [2] Computer Vision Systems Toolbox for MatLab: http://www.mathworks.com/help/vision/index.html, available at 2014-05-30
- [3] Computer Vision System Toolbox User’s Guide, MathWorks, 2015 vision. KalmanFilter class documentation (MatLab): http://www.mathworks.com/help/vision/ref/vision.kalmanfilter-class.html, available at 2015-03-20
- [4] Computer Vision System Toolbox User’s Guide, MathWorks, 2015 configureKalmanFilter function documentation (MatLab): http://www.mathworks.com/help/vision/ref/configurekalmanfilter.html, available at 2015-03-20
- [5] A. Czyżewski, P. Dalka, Moving Objects Detection and Tracking for the Purpose of Multimodal Surveillance System in Urban Areas, [in:] New Directions in Intelligent Interactive Multimedia Studies in Computational Intelligence, vol. 142, pp. 75-84, 2008. DOI: 10.1007/978-3-540-68127-4_8
- [6] V. Einselein, H. Fradi, I. Keller, T. Sikora, J. Dugelay, “Enhancing Human Detection using Crowd Density Measures and an adaptive Correction Filter”, IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 19-24, 2013.
- [7] Heatmap tool from Cognimatics datasheet, http://www.cognimatics.com/downloads/trueview-heatmap-product-sheet.pdf, available at 2014-11-27
- [8] K. Kopaczewski, M. Szczodak, A. Czyżewski, H. Krawczyk, “A method for counting people attending large public events”, Multimedia Tools and Applications, 2013 (online). DOI: 10.1007/s11042-013-1628-0
- [9] C. Lijun, H. Kaiqi, “Video-based crowd density estimation and prediction system for wide-area surveillance”, China Communications, vol.10, no.5, pp.79-88, 2013
- [10] S. F. Lin, J. Y. Chen, H. X. Chao, “Estimation of Number of People in Crowded Scenes Using Perspective Transformation”, IEEE Transactions on Systems, Man, Cybernetics - Part A: Systems and Humans, vol. 31, no. 6, pp. 645-654, 2001.
- [11] A. Marana, S. Velastin, L. Costa, R. Lotufo, “Estimation of crowd density using image processing”, Image Processing for Security Applications, Digest No.: 1997/074, pp 11/1–11/8, 1997.
- [12] T. Marciniak, A. Chmielewska, A. Dabrowski, A. Malina, “People counting vision system based on ARM processor programmed using Simulink environment”, Electronics – constructions, technologies, applications, pp. 55-59, 2014.
- [13] T. Marciniak, A. Dabrowski, A. Chmielewska, M. Nowakowski, “Real-Time Bi-Directional People Counting Using Video Blob Analysis” IEEE New Trends in Audio and Video / Signal Processing Algorithms, Architectures, Arrangements and Applications, pp. 161-166, 2012.
- [14] MxAnalytix tool for map creation and people counting: http://www.mobotix.com/eng_AU/Support/Manuals/Software2/Compact-Guides, available at 2014-11-27.
- [15] The NV-GS500 camera from Panasonic specifications: http://panasonic.net/avc/camcorder/dv/global/products/nv-gs500/specifications.html, available at 2014-11-27
- [16] M. Parzych, A. Chmielewska, T. Marciniak, A. Dąbrowski, “New Approach to People Density Estimation based on Video Surveillance”, International SPA Conference, pp. 94-99, 2014.
- [17] M. Parzych, A. Chmielewska, T. Marciniak, A. Dąbrowski, A. Chrostowska, M. Klincewicz, “Automatic people density maps generation with the use of movement detection analysis”, International Conference on Human-System Interaction, pp.26-31, 2013.
- [18] M. Patzold, R. H. Evangelio, T. Sikora, “Counting people in crowded enviroments by fusion of shape and motion information”, IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 157-164, 2010.
- [19] PETS 2009 database: http://www.cvg.rdg.ac.uk/PETS2009/a.html, available at 2014-05-30
- [20] H. Rahmalan, M. Nixon, J. Carter, “On Crowd Density Estimation for Surveillance”, The Institution of Engineering and Technology Conference on Crime and Security, pp.540-545, 2006.
- [21] M. Rodriguez, I. Laptev, J. Sivic, J. Audibert, “Density-aware person detection and tracking in crowds”, IEEE International Conference on Computer Vision, pp. 2423-2430, 2001.
- [22] H. Sharif, N. Ihaddedene, C. Djeraba, “Crowd Behavior Monitoring on the Escalation Exits:, International Conference on Computer and Information Technology, pp. 194-200, 2008.
- [23] Software for tracking shoppers: http://www.cnet.com/videos/software-tracks-shoppers-to-find-stores-hot-zones/, available at 2014-11-27
- [24] C. Stahlschmidt, A. Gavriilidis, A. Kummert, “Density Measurements from a Top-View Position using a Time-of-Flight Camera”, International Workshop on Multidimensional Systems, pp. 193-198, 2013.
Typ dokumentu
Bibliografia
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