C. Arth, H. Bischof, C. Leistneracc, +. L. Albani, P. Chiesa et al., Tricam-an embedded platform for remote traffic surveillance URL : http:// ieeexplore.ieee.org/abstract/document VIsoc : a smart camera SoC, Conference on Solid-State Circuits Conference Proceedings of the 28th European XXIX [AEL + 18] Mohamed Abouzahir Samir Bouaziz, and Abdelouahed Tajer. Embedding SLAM algorithms : Has it come of age ? Robotics and Autonomous Systems, pp.125-125, 2002.
DOI : 10.1109/cvprw.2006.208
URL : http://www.icg.tugraz.at/pub/pdf/ECVW-CVPR06_Arth.pdf

M. Amy, Les quatre questions de Tinbergen. Linx. Revue des linguistes de l'université Paris X Nanterre, pp.27-33, 2006.
DOI : 10.4000/linx.499
URL : http://journals.openedition.org/linx/pdf/499

D. Aviv, . Stanhill, R. Dror, Z. Roi, J. Danowitz et al., Structured stereo, 2015.

, URL : http://www.google.fr/patents, p.32

J. Boulbaba-ben-amor, A. Su, and . Srivastava, Action recognition using rate-invariant analysis of skeletal shape trajectories. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.38, issue.1, pp.1-13, 2016.

R. Amali-therese-jenifa, C. Akila, and V. Kavitha, Rapid background subtraction from video sequences, 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET), pp.1077-1086, 2012.
DOI : 10.1109/ICCEET.2012.6203780

A. Bandura, Influence of models' reinforcement contingencies on the acquisition of imitative responses., Journal of Personality and Social Psychology, vol.1, issue.6, p.589, 1965.
DOI : 10.1037/h0022070

[. Bauer, A. N. Belbachir, N. Donath, G. Gritsch, B. Kohn et al., Embedded vehicle speed estimation system using an asynchronous temporal contrast vision sensor URL : http://dl.acm.org/citation.cfm? Effects of obesity and sex on the energetic cost and preferred speed of walking, Journal of Applied Physiology, vol.100, issue.12, pp.34-34390, 2006.
DOI : 10.1186/1687-3963-2007-082174

M. Bramberger, J. Brunner, B. Rinner, and H. Schwabach, Realtime video analysis on an embedded smart camera for traffic surveillance, Real- Time and Embedded Technology and Applications Symposium, 2004.
DOI : 10.1109/rttas.2004.1317262

X. Bramberger, A. Doblander, A. Maier, B. Rinner, and H. Schwabach, Distributed embedded smart cameras for surveillance applications URL : http://ieeexplore.ieee.org/abstract/ document, RTAS 2004. 10th IEEE XXIX [BE06] James Black and Tim Ellis. Multi camera image tracking. Image and Vision Computing, pp.174-18168, 2006.
DOI : 10.1109/mc.2006.55

D. Bergmann, New approach for automatic surface reconstruction with coded light, SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation International Society for Optics and Photonics, pp.2-9, 1995.
DOI : 10.1117/12.216931

, URL : http://proceedings.spiedigitallibrary.org/proceeding. aspx?articleid=1007846, p.24

K. Bernardin, A. Elbs, and R. Stiefelhagen, Multiple object tracking performance metrics and evaluation in a smart room environment, Sixth IEEE International Workshop on Visual Surveillance, 2006.

L. Kim, A. C. Boyer, and . Kak, Color-encoded structured light for rapid active ranging, IEEE Transactions on Pattern Analysis and Machine Intelligence, issue.1, pp.14-284767869, 1987.

D. Br??i´br??i´c and T. Kanda, Changes in Usage of an Indoor Public Space: Analysis of One Year of Person Tracking, IEEE Transactions on Human-Machine Systems, vol.45, issue.2, pp.228-237, 2015.
DOI : 10.1109/THMS.2014.2374172

D. Br??i´br??i´c, T. Kanda, T. Ikeda, and T. Miyashita, Person Tracking in Large Public Spaces Using 3-D Range Sensors, IEEE Transactions on Human-Machine Systems, vol.43, issue.6, pp.522-534, 2013.
DOI : 10.1109/THMS.2013.2283945

L. Lobna-ben-khelifa, J. Maggiani, F. Quinton, and . Berry, Ant-Cams Network, Proceedings of the 10th International Conference on Distributed Smart Camera, ICDSC '16, pp.104-109
DOI : 10.1109/JPROC.2008.928932

. J. Blm-+-], X. Boice, C. Lu, G. Margi, G. Stanek et al., Meerkats : A power-aware, self-managing wireless camera network for wide area monitoring

, Proc. Workshop on Distributed Smart Cameras, pp.393-422

B. , S. Beucher, and F. Meyer, The morphological approach to segmentation : the watershed transformation URL : https, URL Optical Engineering, vol.34, pp.433-433, 1992.

, Segmentation-The-Watershed-Transformation-Mathematical-Morphology-in-Image-Proces pdf, p.66

R. Sagi-ben-moshe, M. Kimmel, and . Bronstein, Method and system for structured light 3d camera, U.S. Classification, vol.348369, 2012.

, URL : http://www.google.fr/patents, p.32

K. Berger, S. Meister, R. Nair, and D. Kondermann, A state of the art report on kinect sensor setups in computer vision In Time-of-Flight and Depth Imaging, Sensors, Algorithms, and Applications, pp.257-272978, 1007.

R. Benenson, M. O. Hosang, and B. Schiele, Ten Years of Pedestrian Detection, What Have We Learned?, European Conference on Computer Vision, pp.613-627, 2014.
DOI : 10.1007/978-3-319-16181-5_47

J. L. Bovet, Position de l'éthologie au sein des sciences du comportement, pp.474-482, 1964.

A. Bevilacqua, L. D. Stefano, and P. Azzari, People Tracking Using a Time-of-Flight Depth Sensor, 2006 IEEE International Conference on Video and Signal Based Surveillance, 2006.
DOI : 10.1109/AVSS.2006.92

, AVSS'06. IEEE International Conference on, pp.89-89, 2006.

C. Bobda and S. Velipasalar, Distributed Embedded Smart Cameras : Architectures, Design and Applications
DOI : 10.1007/978-1-4614-7705-1

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2001.
DOI : 10.1109/34.969114

C. Chang and S. Chatterjee, Quantization error analysis in stereo vision, [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers, pp.1037-1041, 1992.
DOI : 10.1109/ACSSC.1992.269140

Y. Chang, S. Chen, and J. Huang, A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities, Research in Developmental Disabilities, vol.32, issue.6, pp.2566-2570, 2011.
DOI : 10.1016/j.ridd.2011.07.002

C. Chen, T. Chen, D. Wang, and T. Chen, A cost-effective people-counter for a crowd of moving people based on two-stage segmentation, Journal of Information Hiding and Multimedia Signal Processing, vol.3, issue.1, pp.12-25, 2012.

R. Hummel, Experiments with the intensity ratio depth sensor. Computer vision, graphics, and image processing, pp.337-358, 1985.

, URL : http://www.sciencedirect.com/science, p.24

C. Chen, Y. Hung, C. Chiang, and J. Wu, Range data acquisition using color structured lighting and stereo vision, Image and Vision Computing, vol.15, issue.6, pp.445-456, 1924.
DOI : 10.1016/S0262-8856(96)01148-1

X. Chen, Design of Many-Camera Tracking Systems for Scalability and Efficient Resource Allocation, p.9, 2002.

T. Chen, An automatic bi-directional passing-people counting method based on color image processing, Procs. 37th Inter Carnahan Conf. on Security Technology, pp.200-207, 2003.

M. Shahzad and C. , Efficient Human Activity Recognition in Large Image and Video Databases, 2014.

, URL : https://www.researchgate.net/profile/Muhammad_Shahzad_Cheema/ publication

. Clc-+-13-]-xiujuan, G. Chai, X. Li, M. Chen, G. Zhou et al., Visualcomm A tool to support communication between deaf and hearing persons with the kinect, Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility, p.76, 2013.

N. Dalal, Finding people in images and videos URL : https://tel.archives-ouvertes. fr/tel-00390303, Video Analytics for Audience Measurement, 2006.

F. Dias, F. Berry, J. Sérot, and F. Marmoiton, Hardware, design and implementation issues on a FPGA-based smart camera ICDSC'07, Distributed Smart Cameras First ACM/IEEE International Conference on, pp.20-26, 2007.

, XXIX

C. Dal-mutto, P. Zanuttigh, and G. M. Cortelazzo, Time-of-flight cameras and microsoft Kinect? URL : https: //books.google.fr/books?hl=en&lr=&id=0ga3V4JBYmIC&oi=fnd&pg=PR3& dq=carlo+dal+mutto&ots=G51lZ0nV1s&sig=cwp5RRFPbZ87Rsr9Friqsafx5kM, p.21, 2012.

L. D. , S. , and A. Bulgarelli, A simple and efficient connected components labeling algorithm, Image Analysis and Processing Proceedings. International Conference on, pp.322-327, 1999.

. Dse-+-13-]-b, J. Dieber, L. Simonjan, B. Esterle, G. Rinner et al., Ella Middleware for multi-camera surveillance in heterogeneous visual sensor networks, Seventh International Conference on Distributed Smart Cameras (ICDSC), pp.1-6, 2013.

[. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2005.
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512

H. Dwb-+-15-]-maxime-devanne, S. Wannous, P. Berretti, M. Pala, A. D. Daoudi et al., 3-D human action recognition by shape analysis of motion trajectories on Riemannian manifold. Cybernetics, IEEE Transactions on, vol.45, issue.7, pp.1340-1352, 2015.

P. Dollár, C. Wojek, B. Schiele, and P. Perona, Pedestrian detection: A benchmark, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.304-311, 2009.
DOI : 10.1109/CVPR.2009.5206631

P. Dollar, C. Wojek, B. Schiele, and P. Perona, Pedestrian detection : An evaluation of the state of the art. Pattern Analysis and Machine Intelligence, IEEE Trans. on, vol.34, issue.4, pp.743-761, 2012.

M. Enzweiler and D. M. Gavrila, Monocular Pedestrian Detection: Survey and Experiments, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, pp.312179-2195, 2009.
DOI : 10.1109/TPAMI.2008.260

A. Ess, B. Leibe, K. Schindler, and L. Van-gool, A mobile vision system for robust multi-person tracking, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-84587581, 2008.
DOI : 10.1109/CVPR.2008.4587581

L. Esterle, P. R. Lewis, X. Yao, and B. Rinner, Socio-economic vision graph generation and handover in distributed smart camera networks, ACM Transactions on Sensor Networks, vol.10, issue.2, p.20, 2014.
DOI : 10.1145/1177352.1177355

S. Fleck, F. Busch, P. Biber, and W. Straber, 3D Surveillance A Distributed Network of Smart Cameras for Real-Time Tracking and its Visualization in 3D, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06), pp.118-118, 2006.
DOI : 10.1109/CVPRW.2006.6

F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua, Multicamera People Tracking with a Probabilistic Occupancy Map, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.2, pp.267-282, 2008.
DOI : 10.1109/TPAMI.2007.1174

S. Fleck, F. Busch, and W. Stra{\textbackslash}s-ser, Adaptive probabilistic tracking embedded in smart cameras for distributed surveillance in a 3d model, pp.24-24, 2007.

X. Ferreira, Visual analytics techniques for exploration of spatiotemporal data URL : http: //search.proquest.com/openview/61bdc7ad67a4f9c92b71e6aa5635e7fa/1? pq-origsite=gscholar&cbl=18750&diss=y, 2015.

P. F. Felzenszwalb, R. B. Girshick, D. Mcallester, and D. Ramanan, Object Detection with Discriminatively Trained Part-Based Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1627-1645, 2010.
DOI : 10.1109/TPAMI.2009.167

K. Fukunaga and L. Hostetler, The estimation of the gradient of a density function, with applications in pattern recognition, IEEE Transactions on Information Theory, vol.21, issue.1, pp.32-40, 1975.
DOI : 10.1109/TIT.1975.1055330

N. Ferreira, J. T. Klosowski, C. E. Scheidegger, and C. T. Silva, -Means: Clustering Trajectories by Fitting Multiple Vector Fields, Computer Graphics Forum, pp.201-210, 2013.
DOI : 10.1111/j.1467-8659.2009.01440.x

H. Fu, H. Ma, and L. Liu, Robust Human Detection with Low Energy Consumption in Visual Sensor Network, 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks, pp.91-97, 2011.
DOI : 10.1109/MSN.2011.84

P. Felzenszwalb, D. Mcallester, and D. Ramanan, A discriminatively trained, multiscale, deformable part model In Computer Vision and Pattern Recognition, CVPR 2008. IEEE Conference on, pp.1-8, 2008.

H. Fu, H. Ma, and H. Xiao, Real-time accurate crowd counting based on RGB-D information, 2012 19th IEEE International Conference on Image Processing, pp.2685-2688, 2012.
DOI : 10.1109/ICIP.2012.6467452

A. David, J. Forsyth, and . Ponce, Computer vision : a modern approach, 2002.

A. Fitzgibbon, M. Pilu, and R. B. Fisher, Direct least square fitting of ellipses. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.21765658, issue.5, pp.476-480, 1999.

G. , D. F. Glas, D. Brscic, T. Miyashita, and N. Hagita, SNAPCAT 3d : Calibrating networks of 3d range sensors for pedestrian tracking, 2015 IEEE International Conference on Robotics and Automation (ICRA), pp.712-719, 2015.

F. Gal?-aík and R. Gargalík, Real-Time Depth Map Based People Counting, Advanced Concepts for Intelligent Vision Systems, pp.330-341, 2013.

P. Michael and . Gibbens, Caldag 2013 : An Interpretive Manual and Checklist. International Code Council, p.62, 2013.

A. Geiger, P. Lenz, C. Stiller, and R. Urtasun, Vision meets Robotics : The KITTI Dataset URL : http://ijr.sagepub.com/content, The International Journal of Robotics Research, vol.22, issue.51, pp.027836491349129710-1177, 2013.
DOI : 10.1177/0278364913491297
URL : http://ttic.uchicago.edu/~rurtasun/publications/geiger_et_al_ijrr13.pdf

A. Gomez-marin, J. J. Paton, A. R. Kampff, R. M. Costa, and Z. F. Mainen, Big behavioral data : psychology, ethology and the foundations of neuroscience URL : https, Nature neuroscience, vol.14, issue.112, pp.1455-1462, 2014.

C. C. Gordon, R. A. Walker, I. Tebbetts, J. T. Mcconville, B. Bradtmiller et al., Anthropometric Survey of US Army Personnel-Methods and Summary Statistics, p.72, 1988.

S. P. Hoogendoorn and W. Daamen, Design assessment of Lisbon transfer stations using microscopic pedestrian simulation, WIT Transactions on The Built Environment, vol.74, p.114, 2004.

D. Helbing and A. Johansson, Pedestrian, Crowd and Evacuation Dynamics, Encyclopedia of Complexity and Systems Science, pp.6476-6495, 2009.
DOI : 10.1007/978-1-4419-7695-6_37
URL : http://arxiv.org/pdf/1309.1609.pdf

P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox, RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments, The International Journal of Robotics Research, vol.1883, issue.5, pp.647-663, 2012.
DOI : 10.1006/cviu.1999.0832

D. Helbing and P. Molnár, Social force model for pedestrian dynamics, Physical Review E, vol.206, issue.5, pp.4282-4286, 1995.
DOI : 10.1016/0378-4371(94)90312-3
URL : http://arxiv.org/pdf/cond-mat/9805244v1.pdf

S. Hengstler, D. Prashanth, S. Fong, and H. Aghajan, MeshEye, Proceedings of the 6th international conference on Information processing in sensor networks , IPSN '07, pp.360-369
DOI : 10.1145/1236360.1236406

J. Heikkila and O. Silvén, A four-step camera calibration procedure with implicit image correction, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.1106-1112, 1997.
DOI : 10.1109/CVPR.1997.609468

A. Thomas, J. Henzinger, and . Sifakis, The Embedded Systems Design Challenge, FM 2006 : Formal Methods, number 4085 in Lecture Notes in Computer Science, pp.1-15, 1007.

J. Han, L. Shao, D. Xu, and J. Shotton, Enhanced computer vision with microsoft kinect sensor : A review, Cybernetics, IEEE Transactions on, vol.43, issue.5, pp.1318-1334, 2013.

J. A. Jennings and W. N. Charman, Depth resolution in stereoscopic systems, Applied Optics, vol.33, issue.22, pp.5192-5196, 1994.
DOI : 10.1364/AO.33.005192

N. Kirchner, A. Alempijevic, X. Dai, P. Plöger, and R. K. Venkat, A robust people detection, tracking, and counting system, International Conference on Robotics and Automation. IEEE, pp.27-54, 2014.

R. Kleihorst, A. Abbo, B. Schueler, and A. Danilin, Camera mote with a high-performance parallel processor for real-time frame-based video processing ICDSC'07 Virgona. Head-to-shoulder signature for person recognition, Distributed Smart Cameras First ACM/IEEE International Conference on 2012 IEEE International Conference on Robotics and Automation (ICRA), pp.109-116, 2007.
DOI : 10.1109/icdsc.2007.4357513

B. Khaleghi, S. Ahuja, and Q. Wu, An improved real-time miniaturized embedded stereo vision system (MESVS-II) In Computer Vision and Pattern Recognition Workshops, CVPRW'08. IEEE Computer Society Conference on, pp.1-8, 2008.
DOI : 10.1109/cvprw.2008.4563144
URL : http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/WorkShops/data/papers/195.pdf

J. Kim, K. Choi, B. Choi, and S. Ko, Real-time visionbased people counting system for the security door, International Technical Conference on Circuits/Systems Computers and Communications, pp.1416-1419, 2002.

[. Kirchner, S. Caraian, P. Colborne-veel, and M. Zeibots, Influencing Passenger Egress to Reduce Congestion at Rail Stations, 2015.

, URL : https://pdfs.semanticscholar.org/538b/ 2dbb3b29e8492e9bab0c48a196c2e070a82d.pdf, p.115

[. Krumm, S. Harris, B. Meyers, B. Brumitt, M. Hale et al., Multi-camera multi-person tracking for EasyLiving, Proceedings Third IEEE International Workshop on Visual Surveillance, pp.3-10, 2000.
DOI : 10.1109/VS.2000.856852

R. Kitchin, The real-time city? Big data and smart urbanism, GeoJournal, vol.50, issue.1, pp.1-14, 2014.
DOI : 10.1007/978-3-642-20898-0_31
URL : http://eprints.maynoothuniversity.ie/5625/1/RK-Real-time-City.pdf

C. G. Keller, D. F. Llorca, and D. M. Gavrila, Dense Stereo-Based ROI Generation for Pedestrian Detection, Joint Pattern Recognition Symposium, pp.81-90, 2009.
DOI : 10.1109/6979.892151
URL : http://gavrila.net/Publications/dagm09_keller.pdf

M. Kytö, M. Nuutinen, and P. Oittinen, Method for measuring stereo camera depth accuracy based on stereoscopic vision, p.78640, 2011.

T. Kanade and M. Okutomi, A stereo matching algorithm with an adaptive window : Theory and experiment. IEEE transactions on pattern analysis and machine intelligence, pp.920-932, 1994.

Q. Li, M. Biswas, M. R. Pickering, and M. R. Frater, Accurate depth estimation using structured light and passive stereo disparity estimation, 2011 18th IEEE International Conference on Image Processing, pp.969-972, 2011.
DOI : 10.1109/ICIP.2011.6116723

C. Lange, E. Chang, B. Suma, A. S. Newman, M. Rizzo et al., Development and evaluation of low cost game-based balance rehabilitation tool using the microsoft kinect sensor, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1831-1834, 2011.
DOI : 10.1109/IEMBS.2011.6090521

J. Lee, J. Han, and K. Whang, Trajectory clustering, Proceedings of the 2007 ACM SIGMOD international conference on Management of data , SIGMOD '07, pp.593-604, 2007.
DOI : 10.1145/1247480.1247546

J. Liu, Y. Liu, Y. Cui, and Y. Chen, Real-time human detection and tracking in complex environments using single RGBD camera, 2013 IEEE International Conference on Image Processing, pp.3088-3092, 2013.
DOI : 10.1109/ICIP.2013.6738636

D. Lefloch, R. Nair, F. Lenzen, H. Schäfer, L. Streeter et al., Technical Foundation and Calibration Methods for Time-of-Flight Cameras, Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications, pp.3-24978, 1007.
DOI : 10.1007/978-3-642-44964-2_1

[. Lu, Image process apparatus International Classification H04N13/02, H04N13/00 ; Cooperative Classification H04N13/0271, 2015.

, URL : http://www.google.fr/patents, p.31

C. Loop and Z. Zhang, Computing rectifying homographies for stereo vision, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.125-131, 1999.
DOI : 10.1109/CVPR.1999.786928

G. Liu, Y. Zhang, L. Liu, Y. Tian, and . Chen, An ultra-fast human detection method for color-depth camera, Journal of Visual Communication and Image Representation, vol.31, issue.57, pp.177-185, 2015.
DOI : 10.1016/j.jvcir.2015.06.014

C. Migniot and F. Ababsa, 3D Human Tracking from Depth Cue in a Buying Behavior Analysis Context, Computer Analysis of Images and Patterns, pp.482-489, 2013.
DOI : 10.1007/978-3-642-40261-6_58
URL : https://hal.archives-ouvertes.fr/hal-00845548

C. Migniot and F. Ababsa, Hybrid 3D???2D human tracking in a top view, Journal of Real-Time Image Processing, vol.1, issue.4, pp.769-784, 2016.
DOI : 10.1109/CVPR.2012.6247907
URL : https://hal.archives-ouvertes.fr/hal-01007424

S. Mattoccia, Stereo Vision Algorithms for FPGAs, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.636-641, 2013.
DOI : 10.1109/CVPRW.2013.96

B. Moorhead, C. Smart, . For-machine-vision, and . Applications, Kalman filter-based algorithms for estimating depth from image sequences, Image Processing and Its Applications Seventh International Conference on, pp.865-869209, 1989.

M. Morel, R. Kulpa, A. Sorel, C. Achard, and S. Dubuisson, Automatic and Generic Evaluation of Spatial and Temporal Errors in Sport Motions, 11th International Conference on Computer Vision Theory and Applications, pp.542-551, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01373822

, URL

S. Mattoccia and P. Macri, A Real Time 3D Sensor for Smart Cameras, Proceedings of the International Conference on Distributed Smart Cameras, ICDSC '14, p.29
DOI : 10.1016/j.micpro.2012.02.014

S. Mattoccia and M. Poggi, A passive RGBD sensor for accurate and real-time depth sensing self-contained into an FPGA, Proceedings of the 9th International Conference on Distributed Smart Camera, ICDSC '15, pp.146-151, 2015.
DOI : 10.1007/BFb0028345

H. Medeiros, J. Park, and A. Kak, A Light-Weight Event-Driven Protocol for Sensor Clustering in Wireless Camera Networks, 2007 First ACM/IEEE International Conference on Distributed Smart Cameras, pp.203-210, 2007.
DOI : 10.1109/ICDSC.2007.4357525

, Characterizing energy consumption in a visual sensor network testbed The Kinect : a low-cost, high-resolution, short-range 3d camera, Testbeds and Research Infrastructures for the Development of Networks and Communities 2nd International Conference on Earth Surface Processes and Landforms, pp.8-926, 2006.

R. D. Macdougall, B. Scherrer, and S. Don, Development of a tool to aid the radiologic technologist using augmented reality and computer vision URL : https, Pediatr Radiol, pp.1-5, 2017.

J. Munkres, Algorithms for the Assignment and Transportation Problems, Journal of the Society for Industrial and Applied Mathematics, vol.5, issue.1, pp.32-38, 1957.
DOI : 10.1137/0105003

L. Neri, G. Adorante, G. Brighetti, and E. Franciosi, Postural rehabilitation through Kinect-based biofeedback, 2013 International Conference on Virtual Rehabilitation (ICVR), pp.218-219, 2013.
DOI : 10.1109/ICVR.2013.6662110

S. Nair, M. Meister, M. Lambers, H. Balda, A. Hofmann et al., Ground truth for evaluating time of flight imaging In Time-of-Flight and Depth Imaging, Sensors, Algorithms, and Applications, pp.52-74978, 1007.

T. Nam and T. A. Pardo, Conceptualizing smart city with dimensions of technology, people, and institutions, Proceedings of the 12th Annual International Digital Government Research Conference on Digital Government Innovation in Challenging Times, dg.o '11, pp.282-291, 2011.
DOI : 10.1145/2037556.2037602

A. Url,

E. Luis, C. Navarro-serment, M. Mertz, and . Hebert, Pedestrian Detection and Tracking Using Three-dimensional LADAR Data URL : http://ijr.sagepub.com, The International Journal of Robotics Research, vol.18, 2010.

W. Ouyang and X. Wang, Joint Deep Learning for Pedestrian Detection, 2013 IEEE International Conference on Computer Vision, pp.2056-2063, 2013.
DOI : 10.1109/ICCV.2013.257

A. Ozcan, Mobile phones democratize and cultivate next-generation imaging, diagnostics and measurement tools, Lab Chip, vol.7, issue.5, pp.3187-319410, 2014.
DOI : 10.1021/nn500614k
URL : http://europepmc.org/articles/pmc4117730?pdf=render

E. Potetsianakis, E. Ksylakis, and G. Triantafyllidis, A Kinect-based framework for better user experience in real-time audiovisual content manipulation, 2014 International Conference on Telecommunications and Multimedia (TEMU), pp.238-242, 2014.
DOI : 10.1109/TEMU.2014.6917767

A. Panangadan, M. Mataric, and G. Sukhatme, Detecting anomalous human interactions using laser range-finders. In Intelligent Robots and Systems, Proceedings. 2004 IEEE/RSJ International Conference on, pp.2136-2141, 2004.
DOI : 10.1109/iros.2004.1389725

D. Pagliari and L. Pinto, Calibration of Kinect for Xbox One and Comparison between the Two Generations of Microsoft Sensors, Sensors, vol.37, issue.11, pp.27569-27589, 2015.
DOI : 10.1109/34.121791

Z. Qiuyu, T. Li, J. Yiping, and D. Wei-jun, A novel approach of counting people based on stereovision and DSP, The 2nd Inter. Conf. on Computer and Automation Engineering (ICCAE), pp.81-84, 2010.

C. Rougier, E. Auvinet, J. Rousseau, M. Mignotte, and J. Meunier, Fall Detection from Depth Map Video Sequences, Toward Useful Services for Elderly and People with Disabilities, pp.121-128, 2011.
DOI : 10.1109/ROBOT.2007.363041
URL : http://www.iro.umontreal.ca/%7Emignotte/Publications/icost11.pdf

M. Rauter, Reliable Human Detection and Tracking in Top-View Depth Images, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.529-534, 2013.
DOI : 10.1109/CVPRW.2013.84

M. Rossi and A. Bozzoli, Tracking and counting moving people, Proceedings of 1st International Conference on Image Processing, pp.212-216, 1994.
DOI : 10.1109/ICIP.1994.413857
URL : http://tev.fbk.eu/TeV/Publications/RosBoz94.pdf

[. Rahimi, R. Baer, O. I. Iroezi, J. C. Garcia, J. Warrior et al., Cyclops, Proceedings of the 3rd international conference on Embedded networked sensor systems , SenSys '05, pp.192-204, 2015.
DOI : 10.1145/1098918.1098939

Z. Tomori and R. Gargalik, Object tracking in 3d using depth map, pp.28-31

A. Rowe, A. G. Goode, D. Goel, and I. Nourbakhsh, Cmucam3 : An open programmable embedded vision sensor Firefly mosaic : A vision-enabled wireless sensor networking system, XXIX [RGR] Anthony Rowe, Dhiraj Goel, and Raj Rajkumar Real-time systems symposium XXIX [RJQ07] B. Rinner, M. Jovanovic, and M. Quaritsch. Embedded Middleware on Distributed Smart Cameras IEEE International Conference on Acoustics, Speech and Signal Processing -ICASSP '07, pp.459-468, 1109.

C. Rudloff, T. Matyus, S. Seer, and D. Bauer, Can Walking Behavior be Predicted?: Analysis of Calibration and Fit of Pedestrian Models, Transportation Research Record: Journal of the Transportation Research Board, vol.2264, issue.1, pp.101-109, 2011.
DOI : 10.1016/0191-2607(87)90016-1

J. Zhou-ren, J. Meng, Z. Yuan, and . Zhang, Robust hand gesture recognition with kinect sensor, Proceedings of the 19th ACM international conference on Multimedia, pp.759-760, 2011.

A. Rakhmadi, Z. Nur, A. Othman, . Bade, S. Mohd et al., Connected Component Labeling Using Components Neighbors-Scan Labeling Approach, Journal of Computer Science, vol.6, issue.10, p.1099, 2010.
DOI : 10.3844/jcssp.2010.1099.1107
URL : http://thescipub.com/pdf/10.3844/jcssp.2010.1099.1107

M. Reisslein, B. Rinner, and A. Roy-chowdhury, Smart Camera Networks, Computer, vol.47, issue.5, pp.23-25, 2014.

R. Radu-bogdan, Semantic 3D Object Maps for Everyday Manipulation in Human Living Environments, TECHNISCHE UNIVERSITÄT MÜNCHEN, vol.35, p.107, 2006.

B. Rinner and W. Wolf, An Introduction to Distributed Smart Cameras, Proceedings of the IEEE, vol.96, issue.10, pp.1565-1575, 2008.
DOI : 10.1109/JPROC.2008.928742

B. Rinner and T. Winkler, Privacy-protecting Smart Cameras, Proceedings of the International Conference on Distributed Smart Cameras, ICDSC '14, p.40
DOI : 10.1109/JPROC.2008.928763

A. and 2. Url,

T. Bernhard-rinner, W. Winkler, M. Schriebl, W. Quaritsch, and . Wolf, The evolution from single to pervasive smart cameras, Distributed Smart Cameras Second ACM/IEEE International Conference on, pp.1-10, 2008.

L. Spinello and K. O. Arras, People detection in RGB-D data, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3838-3843, 2011.
DOI : 10.1109/IROS.2011.6095074

S. Seer, N. Brändle, and C. Ratti, Kinects and human kinetics : a new approach for studying crowd behavior. arXiv preprint arXiv :1210.2838, p.114, 2012.

S. Seer, N. Brändle, and C. Ratti, Kinects and human kinetics : A new approach for studying pedestrian behavior. Transportation research part C : emerging technologies, pp.212-228, 2014.

J. Segen, A camera-based system for tracking people in real time, Proceedings of 13th International Conference on Pattern Recognition, pp.63-67, 1996.
DOI : 10.1109/ICPR.1996.546795

P. Sermanet, K. Kavukcuoglu, S. Chintala, and Y. Lecun, Pedestrian Detection with Unsupervised Multi-stage Feature Learning, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.3626-3633, 2013.
DOI : 10.1109/CVPR.2013.465
URL : http://arxiv.org/pdf/1212.0142

A. Schadschneider, W. Klingsch, H. Klüpfel, T. Kretz, C. Rogsch et al., Evacuation dynamics : Empirical results, modeling and applications, Extreme Environmental Events, pp.517-550, 2011.
DOI : 10.1007/978-1-4419-7695-6_29

R. Sabzevari and D. Scaramuzza, Monocular simultaneous multi-body motion segmentation and reconstruction from perspective views, 2014 IEEE International Conference on Robotics and Automation (ICRA), pp.23-30, 2014.
DOI : 10.1109/ICRA.2014.6906585

Y. Shi and T. Tsui, An FPGA-Based Smart Camera for Gesture Recognition in HCI Applications, Asian conference on Computer vision, pp.718-727
DOI : 10.1007/978-3-540-76386-4_68

, XXIX

L. Spinello, R. Triebel, and R. Siegwart, Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.1823-1829, 2008.
DOI : 10.1109/IROS.2008.4651109

R. Szeliski, URL : http://www.springer.com/us/book/9781848829343 On the detection of dominant points on digital curves, IEEE Transactions on pattern analysis and machine intelligence, vol.18, issue.1078, pp.11859-872, 1989.

T. Teixeira, G. Dublon, and A. Savvides, A survey of humansensing : Methods for detecting presence, count, location, track, and identity

, URL : http, ACM Computing Surveys, vol.5, issue.56, pp.427-450, 2010.

Q. Tian and M. N. Huhns, Algorithms for subpixel registration Computer Vision, Graphics, and Image Processing, pp.220-233, 1986.

N. Tinbergen, On aims and methods of ethology, Ethology, vol.20, issue.4, pp.410-433, 1963.

T. Teixeira, D. Jung, and A. Savvides, Tasking networked CCTV cameras and mobile phones to identify and localize multiple people, Proceedings of the 12th ACM international conference on Ubiquitous computing, Ubicomp '10, pp.213-222, 2010.
DOI : 10.1145/1864349.1864367

C. Tomasi and T. Kanade, Shape and motion from image streams under orthography: a factorization method, International Journal of Computer Vision, vol.4, issue.1, pp.137-154, 1992.
DOI : 10.1007/978-3-642-86940-2_10

, Shape and motion from image streams : a factorization method Classification and evaluation of cost aggregation methods for stereo correspondence, Proceedings of the National Academy of Sciences Computer Vision and Pattern Recognition, pp.9795-9802, 1007.

P. Tsai and M. Shah, Shape from shading using linear approximation, Image and Vision computing, vol.12, issue.8, pp.487-498, 1994.

, VI [TS08] T. Teixeira and A. Savvides. Lightweight People Counting and Localizing for Easily Deployable Indoors WSNs, IEEE Journal of Selected Topics in Signal Processing, vol.2, issue.4, pp.493-502, 2008.

K. Terada, D. Yoshida, S. Oe, and J. Yamaguchi, A method of counting the passing people by using the stereo images, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), pp.338-342, 1999.
DOI : 10.1109/ICIP.1999.822913

S. Ullman, The Interpretation of Structure from Motion, Proceedings of the Royal Society B: Biological Sciences, vol.203, issue.1153, pp.405-426, 1153.
DOI : 10.1098/rspb.1979.0006

P. Viola and M. J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.
DOI : 10.1023/B:VISI.0000013087.49260.fb

P. Viola, M. J. Jones, and D. Snow, Detecting pedestrians using patterns of motion and appearance, Ninth IEEE International Conference on Computer Vision, 2003. Proceedings, pp.734-741, 2003.

A. Virgona, N. Kirchner, and A. Alempijevic, Sensing and perception technology to enable real time monitoring of passenger movement behaviours through congested rail stations, In Australasian Transport Research Forum (ATRF), vol.102, p.115

. Vsc-+-08-]-senem, J. Velipasalar, C. Schlessman, W. H. Chen, J. P. Wolf et al., A scalable clustered camera system for multiple object tracking, EURASIP Journal on Image and Video Processing, p.22, 2008.

P. Vera, D. Zenteno, and J. Salas, Counting Pedestrians in Bidirectional Scenarios Using Zenithal Depth Images, Pattern Recognition, p.84
DOI : 10.1007/978-3-642-38989-4_9

C. Wu, H. Aghajan, and R. Kleihorst, Mapping Vision Algorithms on SIMD Architecture Smart Cameras, 2007 First ACM/IEEE International Conference on Distributed Smart Cameras, p.7, 2007.
DOI : 10.1109/ICDSC.2007.4357502

A. First, IEEE, pp.27-34

J. Ward, The student's guide to cognitive neuroscience XI [web16a] web. ATR | Advanced Telecommunications Research Institute International, p.114, 2015.

, Machines that understand our behavior, 2016.

S. L. Parrot and . Dunk, URL : https://www.parrot.com/us/ business-solutions/parrot-slamdunk, p.31, 2016.

, Point Grey -Brickstream People Counting and Tracking Sensors, p.16, 2016.

, Bidirectional Visitor Counter | 3d People Counting | Queue Management System, 2017.

, Computer vision ? Image processing and analytics | Microsoft Azure URL : https://azure.microsoft.com/en-gb/services/cognitive-services, p.124, 2017.

, CoreMark -Processor Benchmark, 2017.

, Intel® RealSense? Developer Kit for Tablets R200, 2017.

, Kinect pour Xbox One URL : http://www.xbox.com/fr-FR/xbox-one/ kinect/kinect-for-xbox-one, p.33, 2017.

, PS4? Technical Specifications -PlayStation®4 System, 2017.

, ZED -Depth Sensing and Camera Tracking URL : https://www. stereolabs.com, p.32, 2017.

Y. Wu, J. Lim, and M. Yang, Object Tracking Benchmark. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.37, issue.15, pp.1834-1848, 2015.
DOI : 10.1109/tpami.2014.2388226
URL : http://faculty.ucmerced.edu/mhyang/papers/cvpr13_benchmark.pdf

W. Wolf, B. Ozer, and T. Lv, Smart cameras as embedded systems Platforms and architectures for distributed smart cameras, Distributed Embedded Smart Cameras, pp.48-53, 2014.
DOI : 10.1007/978-1-4614-7705-1_1

J. Robert, V. Woodham, V. Vii, S. Wojek, B. Walk et al., Gradient and curvature from the photometric-stereo method, including local confidence estimation URL : https: //www.osapublishing.org/abstract.cfm?uri=josaa-11-11-3050 Multi-cue onboard pedestrian detection, Computer Vision and Pattern Recognition CVPR 2009. IEEE Conference on, pp.3050-3068, 1994.

T. Yahiaoui, C. Meurie, L. Khoudour, and F. Cabestaing, A People Counting System Based on Dense and Close Stereovision URL : https:// link.springer.com/chapter, Image and Signal Processing, pp.59-66, 2008.
DOI : 10.1007/978-3-540-69905-7_7
URL : https://link.springer.com/content/pdf/10.1007%2F978-3-540-69905-7_7.pdf

Y. Wang, S. Velipasalar, and M. Casares, Cooperative Object Tracking and Composite Event Detection With Wireless Embedded Smart Cameras, IEEE Transactions on Image Processing, vol.19, issue.10, pp.2614-2633, 2010.
DOI : 10.1109/TIP.2010.2052278

F. Zanlungo, D. Br??i´br??i´c, and T. Kanda, Pedestrian Group Behaviour Analysis under Different Density Conditions, Transportation Research Procedia, pp.149-158, 2014.
DOI : 10.1016/j.trpro.2014.09.020
URL : https://doi.org/10.1016/j.trpro.2014.09.020

Q. Zheng and R. Chellappa, Estimation of illuminant direction, albedo, and shape from shading A cooperative algorithm for stereo matching and occlusion detection, Computer Vision and Pattern Recognition Proceedings CVPR'91., IEEE Computer Society Conference on, pp.540-545675, 1991.

P. Zanuttigh, G. Marin, C. Dal-mutto, F. Dominio, L. Minto et al., Operating Principles of Time-of-Flight Depth Cameras In Time-of-Flight and Structured Light Depth Cameras, pp.81-113978, 1007.

R. Zhang, P. Tsai, J. E. Cryer, and M. Shah, Shape-from-shading: a survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.8, pp.690-706, 1999.
DOI : 10.1109/34.784284