CNERG IIT Kgp Internship Project - Group Activity Recognition Data Mining Project on StudentLife Data Set :school: :mortar_board: :octocat:
This is my internship project for one and a half months under CNerg Labs, IIT kharagpur.
Student Group Activity Recognition deals with looking into the activities of students of a college based on sensor datas from the Student Life Data Set.
The aim of the project is to see how group formation is taking place, how a particular group evolves over time, how the group breaks over time and correlation with the users of the group with their gpa. Also it aims to finding those users who are not participating in group formation and we can check whether the student has some issues, thus helping us to introspect into the matter.
Recognition of group activities is fundamentally different from single, or multi-user activity recognition in that the goal is to recognize the behavior of the group as an entity, rather than the activities of the individual members within it. Group behavior is emergent in nature, meaning that the properties of the behavior of the group are fundamentally different then the properties of the behavior of the individuals within it, or any sum of that behavior. The main challenges are in modeling the behavior of the individual group members, as well as the roles of the individual within the group dynamic and their relationship to emergent behavior of the group in parallel. Challenges which must still be addressed include quantification of the behavior and roles of individuals who join the group, integration of explicit models for role description into inference algorithms, and scalability evaluations for very large groups and crowds. Group activity recognition has applications for crowd management and response in emergency situations, as well as for social networking and Quantified Self applications.
Entire Documentation Available in Documentation
Main code in group activity recognition folder
Some plots are also being updated in plots folder under various modules.