Kamaljit Kaur

Papers

Total Citations

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About

Kamaljit Kaur is a researcher whose primary focus lies at the intersection of computer vision and surveillance technology, with a particular emphasis on visual object tracking. Her most cited work, "Deep survey on visual object tracking in surveillance environment" (2018), provides a comprehensive literature review that systematically examines diverse tracking methodologies, including feature extraction, shearlet transformation, and particle filter techniques. This survey serves as a foundational resource for researchers and practitioners working to enhance automated surveillance systems, synthesizing key approaches for robust object detection and tracking across varied video environments. While her citation count currently stands at 3, the paper's value lies in its role as a structured guide for navigating the complexities of visual tracking, offering critical insights into the strengths and limitations of different algorithms. Kaur's contribution helps bridge the gap between theoretical techniques and practical surveillance applications, making her work particularly relevant for students and researchers entering the field of video analytics. Her research underscores the ongoing challenges in achieving reliable, real-time object tracking in dynamic, real-world settings.