Human Action Recognition has got many applications in the field of Computer Vision. Apart from surveillance systems, Human Action Recognition is widely being used in the fields of robotics, healthcare, behavior analysis, social networking, education, and video modeling as well. In the last decade, a lot of researchers have proposed new algorithms for the development of HAR systems. This survey paper shows how HAR methods have changed in the last years. Researchers in the early years were using machine learning methods and in last recent years, deep learning gained popularity. There is a need to keep a record of all these developments. These tracks can act as a guide to new researchers. This survey aims to provide them with all the methods that new research can use to solve the problem and will help to show a path for future research. This survey covers all the significant techniques used in the past decade along with it different feature extractors and datasets used are also covered. Models used have been elaborated in detail along its future work scope has also been sighted.