Rajat Khurana

Papers

Total Citations

H-Index

About

Rajat Khurana is a computer vision researcher whose work centers on intelligent video surveillance, with a particular focus on visual object tracking and human activity recognition. In his 2018 deep survey on visual object tracking in surveillance environments, Khurana systematically reviewed techniques including feature extraction, shearlet transformation, and particle filtering, providing a comprehensive framework for understanding how objects can be reliably tracked across varied video types. His parallel survey on human activity recognition (HAR) addressed the growing demand for automated analysis of human behaviors in surveillance footage, cataloging methods for recognizing activities from video sequences. While each of these foundational surveys has garnered 3 citations to date, they represent important early-stage contributions that synthesize and organize knowledge in rapidly evolving fields. Khurana’s work serves as a valuable entry point for researchers and students entering the domains of visual tracking and activity recognition, offering structured overviews of the techniques and challenges that define these areas of computer vision. His surveys help bridge the gap between classical methods and emerging approaches in intelligent surveillance systems.