Abstract
Person recognition has been a challenging research problem for computer vision researchers for many years. A variation of this generic problem is that of identifying the reappearance of the same person in different segments to tag people in a family video. Often we are asked to answer seemingly simple queries such as ‘how many different people are in this video? or ‘find all instances of this person in these videos’. The complexity of the task grows quickly if the video in question includes segments taken at different times, places, lighting conditions, camera settings and distances since these could include substantial variations in resolution, pose, appearance, illumination, background, occlusions, etc. In some scenarios (airports, shopping centers, and city streets) we may have video feeds from multiple cameras with partially overlapping views operating under widely varying lighting and visibility conditions. Yet computer vision systems are challenged to find and track a person of interest as data from such systems have become ubiquitous and concern for security in public spaces has become a growing concern. While this is yet an unsolved challenge, much progress has been made in recent years in developing computer vision algorithms which are the building blocks for person detection, tracking and recognition. We consider several video capture scenarios, discuss the challenges they present for person re-identification and recognition as the complexity of the scene changes, and present pointers to recent research work in relevant computer vision areas in this paper.
Chapter PDF
Similar content being viewed by others
References
Massimo, B., Broggi, A., Cellario, M., Fascioli, A., Lombardi, P., Porta, M.: Artificial vision in road vehicles. Proceedings of the IEEE 90(7), 1258–1271 (2002)
Pavan, T., Chellappa, R., Subrahmanian, V.S., Udrea, O.: Machine recognition of human activities: A survey. IEEE Transactions on Circuits and Systems for Video Technology 18(11), 1473–1488 (2008)
Fakhreddine, K., Alemzadeh, M., Saleh, J.A., Arab, M.N.: Human-computer interaction: Overview on state of the art (2008)
Hammadi, N.-C., McKenna, S.J.: Activity summarisation and fall detection in a supportive home environment. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 4, pp. 323–326. IEEE (2004)
Atrey, P.K., Hossain, M.A., El Saddik, A., Kankanhalli, M.S.: Multimodal fusion for multimedia analysis: a survey. Multimedia Systems 16(6), 345–379 (2010)
Weiming, H., Tan, T., Wang, L., Maybank, S.: A survey on visual surveillance of object motion and behaviors. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 34(3), 334–352 (2004)
Abowd, G.D., Gauger, M., Lachenmann, A.: The Family Video Archive: an annotation and browsing environment for home movies. In: Abowd, G.D. (ed.) Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, pp. 1–8. ACM (2003)
Sohaib, K., Shah, M.: Consistent labeling of tracked objects in multiple cameras with overlapping fields of view. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(10), 1355–1360 (2003)
Roberto, V., Baltieri, D., Cucchiara, R.: People reidentification in surveillance and forensics: A survey. ACM Computing Surveys (CSUR) 46(2), 29 (2013)
Gong, S., Cristani, M., Yan, S., Loy, C.C.: Person Re-Identification. Springer (2014)
Apurva, B.-G., Shah, S.K.: A survey of approaches and trends in person re-identification. Image and Vision Computing 32(4), 270–286 (2014)
EC Funded CAVIAR project/IST 2001 37540, http://homepages.inf.ed.ac.uk/rbf/CAVIAR/
https://www.flickr.com/photos/marshallstudentcenter/3092267497/
Liem, M.C., Gavrila, D.M.: A comparative study on multi-person tracking using overlapping cameras. In: Chen, M., Leibe, B., Neumann, B. (eds.) ICVS 2013. LNCS, vol. 7963, pp. 203–212. Springer, Heidelberg (2013)
Ferryman, J., Ellis, A.: PETS2010: Dataset and challenge. In: Ferryman, J. (ed.) 2010 Seventh IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 143–150. IEEE (2010)
Navneet, D., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886–893. IEEE (2005)
Mykhaylo, A., Roth, S., Schiele, B.: People-tracking-by-detection and people-detection-by-tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8. IEEE (2008)
Bastian, L., Seemann, E., Schiele, B.: Pedestrian detection in crowded scenes. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 878–885. IEEE (2005)
Bo, W., Nevatia, R.: Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors. International Journal of Computer Vision 75(2), 247–266 (2007)
Tao, Z., Nevatia, R.: Tracking multiple humans in complex situations. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(9), 1208–1221 (2004)
Ivana, M., Santini, S., Jain, R.: Video processing and integration from multiple cameras. In: Proceedings of the 1998 Image Understanding Workshop, vol. 6. Morgan-Kaufman, San Francisco (1998)
Jian, Y., Odobez, J.-M.: Multi-Person Bayesian Tracking with Multiple Cameras. Multi-Camera Networks: Principles and Applications 363 (2009)
Sankaranarayanan, A.C., Veeraraghavan, A., Chellappa, R.: Object detection, tracking and recognition for multiple smart cameras. Proceedings of the IEEE 96(10), 1606–1624 (2008)
Jain, A.K., Ross, A.A., Nandakumar, K.: Introduction to biometrics. Springer (2011)
Kuang-Chih, L., Ho, J., Yang, M.-H., Kriegman, D.: Video-based face recognition using probabilistic appearance manifolds. In: Proceedings 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. I–313. IEEE (2003)
Unsang, P., Jain, A.K., Ross, A.: Face recognition in video: Adaptive fusion of multiple matchers. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8. IEEE (2007)
Xiaoming, L., Chen, T.: Video-based face recognition using adaptive hidden markov models. In: Proceedings. 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.1, pp. I–313. IEEE (2003)
Gunturk, B.K., Batur, A.U., Altunbasak, Y., Hayes, M.H., Mersereau, R.M.: Eigenface-domain super-resolution for face recognition. IEEE Transactions on Image Processing 12(5), 597–606 (2003)
Jonathon, P.P., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)
Lee, K.-C., Ho, J., Kriegman, D.: Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(5), 684–698 (2005)
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: DeepFace: Closing the Gap to Human-Level Performance in Face Verification. In: Computer Vision and Pattern Recognition, CVPR (2014)
Hu, J., Lu, J., Tan, Y.-P.: Discriminative Deep Metric Learning for Face Verification in the Wild. In: Computer Vision and Pattern Recognition, CVPR (2014)
Sun, Y., Wang, X., Tang, X.: Deep Learning Face Representation from Predicting 10,000 Classes. Computer Vision and Pattern Recognition, CVPR (2014)
Huang, G.B., Ramesh, M., Berg, T., Learned-miller, E.: Labeled faces in the wild: A database for studying face recognition in un-constrained environments. In: ECCV Workshop on Faces in Real-life Images (2008)
Wolf, L., Hassner, T., Maoz, I.: Face recognition in unconstrained videos with matched background similarity. In: CVPR, pp. 529–534 (2011)
Liu, Z., Sarkar, S.: Simplest representation yet for gait recognition: Averaged silhouette. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 4, pp. 211–214. IEEE (2004)
Olivier, B., Van Droogenbroeck, M.: Frontal-view gait recognition by intra-and inter-frame rectangle size distribution. Pattern Recognition Letters 30(10), 893–901 (2009)
Chen, C., Liang, J., Zhao, H., Hu, H., Tian, J.: Frame difference energy image for gait recognition with incomplete silhouettes. Pattern Recognition Letters 30(11), 977–984 (2009)
Wang, J., She, M., Nahavandi, S., Kouzani, A.: A review of vision-based gait recognition methods for human identification. In: 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 320–327. IEEE (2010)
Chang, K., Bowyer, K.W., Sarkar, S., Victor, B.: Comparison and combination of ear and face images in appearance-based biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1160–1165 (2003)
Chen, H., Bhanu, B.: Human ear recognition in 3D. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4), 718–737 (2007)
Yan, P., Bowyer, K.W.: Biometric recognition using 3D ear shape. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(8), 1297–1308 (2007)
Abaza, A., Ross, A., Hebert, C., Harrison, M.A.F., Nixon, M.S.: A survey on ear biometrics. ACM Computing Surveys (CSUR) 45(2), 22 (2013)
Kinnunen, T., Li, H.: An overview of text-independent speaker recognition: from features to supervectors. Speech Communication 52(1), 12–40 (2010)
Jain, A.K., Park, U.: Facial marks: Soft biometric for face recognition. In: 2009 16th IEEE International Conference on Image Processing (ICIP), pp. 37–40. IEEE (2009)
Lee, J.-E., Jain, A.K., Jin, R.: Scars, marks and tattoos (SMT): Soft biometric for suspect and victim identification. In: Biometrics Symposium, BSYM 2008, pp. 1–8. IEEE (2008)
Wang, X.: Intelligent multi-camera video surveillance: A review. Pattern Recognition Letters 34(1), 3–19 (2013)
Aghajan, H., Cavallaro, A. (eds.): Multi-Camera Networks: Concepts and Applications. Elsevier (2009)
Snavely, N., Seitz, S.M., Szeliski, R.: Modeling the world from internet photo collections. International Journal of Computer Vision 80(2), 189–210 (2008)
Pollefeys, M., Nistér, D., Frahm, J.-M., Akbarzadeh, A., Mordohai, P., Clipp, B., Engels, C., et al.: Detailed real-time urban 3d reconstruction from video. International Journal of Computer Vision 78(2-3), 143–167 (2008)
Akbarzadeh, A., Frahm, J.-M., Mordohai, P., Clipp, B., Engels, C., Gallup, D., Merrell, P., et al.: Towards urban 3D reconstruction from video. In: Akbarzadeh, A.J.-M. (ed.) Third International Symposium on 3D Data Processing, Visualization, and Transmission, pp. 1–8. IEEE (2006)
Strecha, C., von Hansen, H., Van Gool, L., Fua, P., Thoennessen, U.: On benchmarking camera calibration and multi-view stereo for high resolution imagery. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–8. IEEE (2008)
Porikli, F.: Inter-camera color calibration using cross-correlation model function. In: ICIP (2003)
Javed, O., Shafique, K., Shah, M.: Appearance modeling for tracking in multiple non-overlapping cameras. In: CVPR (2005)
Prosser, B., Gong, S., Xiang, T.: Multi-camera Matching Using Bi-Directional Cumulative Brightness Transfer Functions. In: BMVC (2008)
Chen, K.-W., Lai, C.-C., Hung, Y.-P., Chen, C.-S.: An adaptive learning method for target tracking across multiple cameras. In: CVPR (2008)
Vaquero, D.A., Feris, R.S., Tran, D., Brown, L., Hampapur, A., Turk, M.: Attribute-based people search in surveillance environments. In: Vaquero, D.A. (ed.) 2009 Workshop on Applications of Computer Vision (WACV), pp. 1–8. IEEE (2009)
Layne, R., Hospedales, T.M., Gong, S.: Towards person identification and re-identification with attributes. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 402–412. Springer, Heidelberg (2012)
Liu, X., Song, M., Zhao, Q., Tao, D., Chen, C., Bu, J.: Attribute-restricted latent topic model for person re-identification. Pattern Recognition 45(12), 4204–4213 (2012)
Zhao, R., Ouyang, W., Wang, X.: Unsupervised salience learning for person re-identification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3586–3593. IEEE (2013)
Zhao, R., Ouyang, W., Wang, X.: Person re-identification by salience matching. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 2528–2535. IEEE (2013)
Douglas, G., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition, and tracking. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (2007)
Schwartz, W.R., Davis, L.S.: Learning discriminative appearance-based models using partial least squares. In: 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI), pp. 322–329. IEEE (2009)
Avraham, T., Gurvich, I., Lindenbaum, M., Markovitch, S.: Learning implicit transfer for person re-identification. In: Fusiello, A., Murino, V., Cucchiara, R. (eds.) ECCV 2012 Ws/Demos, Part I. LNCS, vol. 7583, pp. 381–390. Springer, Heidelberg (2012)
Wu, Y., Li, W., Minoh, M., Mukunoki, M.: Can feature-based inductive transfer learning help person re-identification? In: ICIP, pp. 2812–2816 (2013)
Layne, R., Hospedales, T.M., Gong, S.: Domain transfer for person re-identification. In: Proceedings of the 4th ACM/IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Stream, pp. 25–32. ACM (2013)
Ma, A.J., Yuen, P.C., Li, J.: Domain transfer support vector ranking for person re-identification without target camera label information. In: 2013 IEEE International Conference on Computer Vision (ICCV), pp. 3567–3574. IEEE (2013)
Gray, D., Brennan, S., Tao, H.: Evaluating appearance models for recognition, reacquisition, and tracking. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (2007)
Zheng, W.-S., Gong, S., Xiang, T.: Associating Groups of People. In: Proc. British Machine Vision Conference (BMVC), London (September 2009)
Dong, S.C., Cristani, M., Stoppa, M., Bazzani, L., Murino, V.: Custom Pictorial Structures for Re-identification. In: BMVC (2011)
Baltieri, D., Vezzani, R., Cucchiara, R.: 3dpes: 3d people dataset for surveillance and forensics. In: Proceedings of the 2011 Joint ACM Workshop on Human Gesture and Behavior Understanding, pp. 59–64. ACM (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Kasturi, R., Ekambaram, R. (2014). Person Reidentification and Recognition in Video. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_35
Download citation
DOI: https://doi.org/10.1007/978-3-319-12568-8_35
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12567-1
Online ISBN: 978-3-319-12568-8
eBook Packages: Computer ScienceComputer Science (R0)