Ranjitha Shenoy

Papers

Total Citations

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About

Ranjitha Shenoy is a robotics researcher whose work focuses on real-time vision-based human-robot interaction, particularly in dynamic environments. Her most cited paper, "Vision-based robotic person following in fast walking" (2014, 5 citations), introduces a novel approach combining shape detection and color histogram matching with adaptive search area techniques. By first detecting a person's head through Canny edge detection and a modified Hough transform, Shenoy's method enables robots to reliably track and follow individuals even during fast-paced movement—a critical capability for applications in assistive robotics, autonomous navigation, and human-robot collaboration. This contribution addresses the challenge of maintaining robust visual tracking under real-world conditions, such as varying lighting and occlusions. While her citation count reflects a niche but impactful contribution, Shenoy's work demonstrates a practical, computationally efficient solution that bridges computer vision and robotics. Her research advances the field of mobile robotics by enhancing robots' ability to interact seamlessly with humans in uncontrolled settings, laying groundwork for future developments in autonomous person-following systems.