Parminder Kaur

Papers

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About

Parminder Kaur is a researcher in computer vision and video analytics, with a primary focus on object detection and tracking technologies. Her most-cited work, the 2014 survey "Object Tracking Techniques for Video Tracking," provides a foundational overview of methods used in surveillance, vehicle navigation, and autonomous robotics. While her citation count is modest, this survey captures a critical moment in the field's development, offering a structured taxonomy of tracking approaches that has informed subsequent research. Kaur's contributions lie in synthesizing complex techniques—such as feature-based tracking, kernel-based methods, and appearance models—into an accessible framework for practitioners. Her work underscores the persistent challenges in real-time tracking, including occlusion handling and computational efficiency. Though early in her citation trajectory, Kaur's survey serves as a valuable entry point for students and engineers entering the domain of video-based object tracking, reflecting her role in documenting and clarifying the state of the art during a period of rapid advancement in computer vision applications.