P. Anandan
Papers
2
Total Citations
48
H-Index
2
About
P. Anandan is a pioneering computer vision researcher whose work has fundamentally shaped how machines perceive and navigate the visual world. His research centers on structure from motion, multi-object tracking, and video analysis, with a particular focus on solving geometric and dynamic vision problems. Anandan’s most influential contribution is his seminal paper on structure and motion from two-dimensional images using a least squares approach, which provided a rigorous mathematical framework for recovering scene geometry and camera motion from multiple views. This work, with 37 citations, addressed a critical problem for indoor mobile robots, enabling them to construct environmental maps from vertical line correspondences. More recently, Anandan has advanced object detection and multi-object tracking by integrating optimized deep convolutional neural networks with unscented Kalman filtering, tackling persistent challenges like occlusion in video surveillance and robotics. His research has had a lasting impact on autonomous systems, bridging classical geometric methods with modern deep learning techniques. Anandan’s work continues to inspire researchers developing robust, real-time vision systems for navigation and scene understanding.
Research Focus
Key Achievements
Top Papers
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