A texture based mani-fold approach for crowd density estimation using Gaussian Markov Random Field
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[1] Neeta Nain,et al. Multi-source approach for crowd density estimation in still images , 2017, 2017 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA).
[2] Ivan Laptev,et al. Density-aware person detection and tracking in crowds , 2011, ICCV.
[3] Luciano da Fontoura Costa,et al. Estimating crowd density with Minkowski fractal dimension , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).
[4] Luciano da Fontoura Costa,et al. Automatic estimation of crowd density using texture , 1998 .
[5] Lei Huang,et al. Crowd density analysis using co-occurrence texture features , 2010, 5th International Conference on Computer Sciences and Convergence Information Technology.
[6] Shenghua Gao,et al. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] A. Marana,et al. On the efficacy of texture analysis for crowd monitoring , 1998, Proceedings SIBGRAPI'98. International Symposium on Computer Graphics, Image Processing, and Vision (Cat. No.98EX237).
[8] G. N. Srinivasan,et al. Statistical Texture Analysis , 2008 .
[9] Song-Chun Zhu,et al. What are Textons? , 2005, International Journal of Computer Vision.
[10] Ramakant Nevatia,et al. Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors , 2007, International Journal of Computer Vision.
[11] Serge J. Belongie,et al. Counting Crowded Moving Objects , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[12] Vijayan Sugumaran,et al. Building knowledge base of urban emergency events based on crowdsourcing of social media , 2016, Concurr. Comput. Pract. Exp..
[13] Anil K. Jain,et al. An Intrinsic Dimensionality Estimator from Near-Neighbor Information , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Sridha Sridharan,et al. Crowd Counting Using Multiple Local Features , 2009, 2009 Digital Image Computing: Techniques and Applications.
[15] L. Li,et al. On pixel count based crowd density estimation for visual surveillance , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..
[16] Tieniu Tan,et al. Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection , 2008, 2008 19th International Conference on Pattern Recognition.
[17] Nuno Vasconcelos,et al. Bayesian Poisson regression for crowd counting , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[18] K. S. Venkatesh,et al. People Counting in High Density Crowds from Still Images , 2015, ArXiv.
[19] Kim-Kwang Raymond Choo,et al. iOS Forensics: How Can We Recover Deleted Image Files with Timestamp in a Forensically Sound Manner? , 2013, 2013 International Conference on Availability, Reliability and Security.
[20] Song-Chun Zhu,et al. What are Textons? , 2002, ECCV.
[21] Robert T. Collins,et al. Marked point processes for crowd counting , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[22] Ognjen Arandjelovic,et al. Crowd Detection from Still Images , 2008, BMVC.
[23] Andrea Vedaldi,et al. Vlfeat: an open and portable library of computer vision algorithms , 2010, ACM Multimedia.
[24] Paul Rad,et al. A Privacy-Aware Architecture at the Edge for Autonomous Real-Time Identity Reidentification in Crowds , 2018, IEEE Internet of Things Journal.
[25] Li Xiaohua,et al. Estimation of Crowd Density Based on Wavelet and Support Vector Machine , 2006 .
[26] Greg Mori,et al. Detecting Pedestrians by Learning Shapelet Features , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[27] David A. McAllester,et al. A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[28] C.-C. Jay Kuo,et al. Texture analysis and classification with tree-structured wavelet transform , 1993, IEEE Trans. Image Process..
[29] Fazilah Haron,et al. CDES: A pixel-based crowd density estimation system for Masjid al-Haram , 2011, Safety Science.
[30] W. Eric L. Grimson,et al. Unsupervised Activity Perception by Hierarchical Bayesian Models , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Xiaogang Wang,et al. Cross-scene crowd counting via deep convolutional neural networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Tommy W. S. Chow,et al. A neural-based crowd estimation by hybrid global learning algorithm , 1999, IEEE Trans. Syst. Man Cybern. Part B.
[33] Shaogang Gong,et al. Feature Mining for Localised Crowd Counting , 2012, BMVC.
[34] Ramakant Nevatia,et al. Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[35] Roberto Cipolla,et al. Unsupervised Bayesian Detection of Independent Motion in Crowds , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[36] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[37] Haroon Idrees,et al. Multi-source Multi-scale Counting in Extremely Dense Crowd Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[38] Anil K. Jain,et al. Markov Random Field Texture Models , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[39] Kim-Kwang Raymond Choo,et al. Data Recovery from Proprietary Formatted Cctv Hard Disks , 2013, IFIP Int. Conf. Digital Forensics.
[40] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[41] Neeta Nain,et al. Crowd Monitoring and Classification: A Survey , 2017 .
[42] Sheng-Fuu Lin,et al. Estimation of number of people in crowded scenes using perspective transformation , 2001, IEEE Trans. Syst. Man Cybern. Part A.
[43] Nuno Vasconcelos,et al. Privacy preserving crowd monitoring: Counting people without people models or tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[44] Jitendra Malik,et al. Recognizing surfaces using three-dimensional textons , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[45] Antoni B. Chan,et al. Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks—Counting, Detection, and Tracking , 2017, IEEE Transactions on Circuits and Systems for Video Technology.
[46] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[47] Pietro Perona,et al. Pedestrian Detection: An Evaluation of the State of the Art , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[48] Xiaochun Cao,et al. Deep People Counting in Extremely Dense Crowds , 2015, ACM Multimedia.
[49] L. Kratz,et al. Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[50] Shaogang Gong,et al. Cumulative Attribute Space for Age and Crowd Density Estimation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[51] ZhangHui,et al. Building knowledge base of urban emergency events based on crowdsourcing of social media , 2016 .
[52] Mao Ye,et al. Fast crowd density estimation with convolutional neural networks , 2015, Eng. Appl. Artif. Intell..
[53] Sergio A. Velastin,et al. Crowd monitoring using image processing , 1995 .
[54] Robert Azencott,et al. Texture Classification Using Windowed Fourier Filters , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[55] Alan Fern,et al. Person count localization in videos from noisy foreground and detections , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[57] Andrew Zisserman,et al. Learning To Count Objects in Images , 2010, NIPS.
[58] Neeta Nain,et al. A Robust Multi-Model Approach for Face Detection in Crowd , 2016, 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS).
[59] Noel E. O'Connor,et al. Fully Convolutional Crowd Counting on Highly Congested Scenes , 2016, VISIGRAPP.