The Computer Vision Group of IIT Madras was started on September 2009 with a vision of building a team of students with deep expertise in the technology of Computer Vision. The idea for the formation of such a club was seeded in 2008 when the IIT Madras team had represented India at the International Aerial Robotics Competition (IARC). CVG which competed against elite teams, from other top Universities in IARC 2009, was acknowledged as the best vision team among all the participating teams.
Being the only club out of which a start-up has grown, CVG has extraordinary mentorship and motivated and committed members, who have completed Industrial Projects by ITC, The Indian Railways, VDime, Eye hospital CHECK and multiple machine learning projects.
- Fun with Faces – This project was a small scale attempt at Snapchat with a few filters which would add certain add ons to your face. The final version used a library called dlib, which provides facial feature points and using a few machine learning algorithms, real time results were achieved.
Initial prototype –
- Rubik’s cube solver – Using images of the sides of a Rubik cube, this project will be able to solve it within seconds and it will give a 3d simulation and the steps required to solve it.
- Expression Morphing – This project could morph expressions to one’s face, to make him smile or frown. It used a few libraries which would help obtain the facial keypoints and after a certain lines of code provided a final image which would have an expression decided by the user.
- Cell Boundary Identification – This project, was a part of Government of India’s innovation challenge. It aims at automated identification of cell boundaries from the pathological slides. This holds a tremendous potential for cancer diagnosis. It involves decomposing a video of the sample into frames and identifying cell boundaries.
- Face Recognition – This project is a part of CFI Jarvis which aims at making the new CFI building smart. This project focuses on the security features of the new building. It will continuously scan the environment and grants access to those who have been registered in the database of users. Future features will include face search through the institute database and alerts in the case of an attempt to breach security protocols.
- Voice App Control – This project, uses one’s voice to control mobile phone apps. By using Natural Language Processing techniques, this app will be able to seamlessly control your phone’s interface.
- AutoCaption – This project, as the name suggests, automatically provides captions to an input image using state of the art neural networks. It also provides hashtags.
- Video Stabilization for UAVs – The primary objective of the project is to ensure proper clarity of a video taken from a moving camera source. This will help in retrieving useful features which otherwise will be rendered useless due to camera shake.
- Evaluation of OMR – Using computer vision and machine learning techniques, one could make the process of evaluating the OMR easier and more accurate compared to the traditional methods that currently exist.