Aditya’s primary interests include feature learning, time series analysis, and trend detection in data. He is Presently working on Machine Learning Algorithms that can be utilised for motion learning. The present focus of the research is on neural network architectures for hand-pose and hand gesture recognition while using low accuracy, low-resolution time of flight camera.
Aditya completed his Masters in Systems and Signal Processing at the University of Southampton, UK at CSPC group which is now the Vision, Learning and Control Group. He completed his Masters thesis on locating curvilinear features in Noisy Bronchial Wall Confocal Images in 2013. Earlier, he completed his Bachelors from the G.B.Pant university Pantnagar in 2010.
A Probablistic Combination of CNN and RNN Estimates for Hand Gesture Based Interaction in Car
16th IEEE International Symposium on Mixed and Augmented Reality (ISMAR) IEEE International Symposium on Mixed and Augmented Reality (ISMAR-17), October 9-13, Nantes, France
Adding Model Constraints to CNN for Top View Hand Pose Recognition in Range Images
Proceedings of the 5th International Conference in Pattern Recognition Applications and Methods ICPRAM 2016 International Conference on Pattern Recognition Applications and Methods (ICPRAM-05), 5th, February 24-26, Rome, Italy
Learning to Fuse: A Deep Learning Approach to Visual-Inertial Camera Pose Estimation
IEEE International Symposium on Mixed and Augmented Reality (ISMAR-2016), September 19-23, Merida, Mexico
Two Phase Classification for Early Hand Gesture Recognition in 3D Top View Data
International Symposium on Visual Computing : Advances in Visual Computing International Conference on Visual Computing (ISVC-16), Advances in Visual Computing, December 12-14, Las Vegas, Nevada, USA