With the availability of high performance processors and GPUs, the place for Machine learning , Deep learning algorithms are growing exponentially. It has become more and more possible to explore the depths of fields like Computer vision with these trends. Detecting humans in video footage using computer vision is one such area. Although human detection is somewhat primitive, using that data to produce various results like recognizing postures, predicting behaviors, predicting paths are very advanced fields and they have very much room left to grow. Various algorithms, approaches are available today to accomplish the above kind of tasks, from classical machine learning , neural networks to statistical approaches like Bayes theorem, Hidden Markov Models, Time series, etc. This paper aims at exploring algorithms and various approaches that have been used by researchers in various scenarios that are related to post processing the data taken from video footages by detecting and analyzing human figures in them.