Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture., {"references":["Gall, J., Rosenhahn, B., Brox, T., & Seidel, H. P. (2010). Optimization\nand filtering for human motion capture. International journal of\ncomputer vision, 87(1-2), 75-92","Pons-Moll, G., Baak, A., Helten, T., Muller, M., Seidel, H. P., &\nRosenhahn, B. (2010). Multisensor-fusion for 3d full-body human\nmotion capture. In Computer Vision and Pattern Recognition (CVPR),\n2010 IEEE Conference on (pp. 663-670). IEEE.","Swaisaenyakorn, S., Kelly, S. W., Young, P. R., & Batchelor, J. C.\n(2012). Evaluation of 3D animated human model from 3D scanner and\nmotion capture to be used in electromagnetic simulator for body-centric\nsystem. In Biomedical Engineering and Informatics (BMEI), 5th\nInternational Conference on (pp. 632-636). IEEE.","Field, M., Pan, Z., Stirling, D., & Naghdy, F. (2011). Human motion\ncapture sensors and analysis in robotics. Industrial Robot: An\nInternational Journal, 38(2), 163-171.","Sigal, L., Balan, A. O., & Black, M. J. (2010). Humaneva: Synchronized\nvideo and motion capture dataset and baseline algorithm for evaluation\nof articulated human motion. International journal of computer vision,\n87(1-2), 4-27.","Keskin, C., Kıraç, F., Kara, Y. E., & Akarun, L. (2013). Real time hand\npose estimation using depth sensors. In Consumer Depth Cameras for\nComputer Vision (pp. 119-137). Springer London.","G. Johnasson, (1973). \"Visual Perception of Biological Motion and a\nModel for Its Analysis.\" Perception Psychophysics 14(2): 201-211.","M. K. Leung and Y.H. Yang (1995). \"First Sight: A Human Body\nOutline Labeling System.\" IEEE Transactions on Pattern Analysis and\nMachine Intelligence 17(4): 359-377.","Sapp, Benjamin, David Weiss, and Ben Taskar. \"Parsing human motion\nwith stretchable models.\" Computer Vision and Pattern Recognition\n(CVPR), 2011 IEEE Conference on. IEEE, 2011.\n[10] Shao, L., Ji, L., Liu, Y., & Zhang, J. (2012). Human action segmentation\nand recognition via motion and shape analysis. Pattern Recognition\nLetters, 33(4), 438-445.\n[11] J. J. a. T. S. H. \". Kuch, \"Vision Based Hand Modeling and Tracking for\nvirtual teleconferencing and telecollaboration,\" in ICCV , 1995.\n[12] J. W. a. A. B. Davis, \"The Representation and Recognition of Action\nUsing Temporal Templates,\" in International Conference on Computer\nVision and, 1995.\n[13] Jiang, Z., Lin, Z., & Davis, L. S. (2012). Recognizing human actions by\nlearning and matching shape-motion prototype trees. Pattern Analysis\nand Machine Intelligence, IEEE Transactions on, 34(3), 533-547.\n[14] Niebles, J. C., Han, B., & Fei-Fei, L. (2010, June). Efficient extraction\nof human motion volumes by tracking. In Computer Vision and Pattern\nRecognition (CVPR), 2010 IEEE Conference on (pp. 655-662). IEEE.\n[15] Li, R., Tian, T. P., Sclaroff, S., & Yang, M. H. (2010). 3d human motion\ntracking with a coordinated mixture of factor analyzers. International\nJournal of Computer Vision, 87(1-2), 170-190.\n[16] Vondrak, M., Sigal, L., & Jenkins, O. C. (2013). Dynamical simulation\npriors for human motion tracking. Pattern Analysis and Machine\nIntelligence, IEEE Transactions on, 35(1), 52-65.\n[17] Stone, E. E., & Skubic, M. (2011, May). Evaluation of an inexpensive\ndepth camera for passive in-home fall risk assessment. In Pervasive\nComputing Technologies for Healthcare (PervasiveHealth), 2011 5th\nInternational Conference on (pp. 71-77). IEEE.\n[18] Aggarwal, J. K., & Ryoo, M. S. (2011). Human activity analysis: A\nreview. ACM Computing Surveys (CSUR), 43(3), 16.\n[19] Raskin, L., Rudzsky, M., & Rivlin, E. (2011). Dimensionality reduction\nusing a Gaussian Process Annealed Particle Filter for tracking and\nclassification of articulated body motions. Computer Vision and Image\nUnderstanding, 115(4), 503-519."]}