Jagdish Lal Raheja

About

Jagdish Lal Raheja is a prominent researcher specializing in computer vision, human-computer interaction, and robotics, with a particular focus on hand gesture recognition and real-time control systems. His work has significantly advanced the field of natural human-machine interaction, accumulating over 500 citations across his most influential publications. Raheja's landmark contribution, "Tracking of Fingertips and Centers of Palm Using KINECT" (2011), garnered 201 citations and established foundational techniques for depth-sensor-based hand tracking in virtual environments. Complementing this, his 2010 paper on real-time robotic hand control through gesture recognition (116 citations) demonstrated a practical, camera-based approach to commanding robotic systems through intuitive hand poses — a breakthrough with profound implications for human-robot interaction. Beyond experimental systems, Raheja has contributed extensively to synthesizing the field through survey papers on soft computing approaches and intelligent interaction methodologies. His geometric and ANN-based methods for calculating finger angles further bridged the gap between computer vision and electromechanical robotics. More recently, his exploration of brain-computer interfaces for Arduino-based robot control reflects a broadening research vision. Raheja's body of work collectively advances accessible, natural interfaces between humans and increasingly intelligent machines.

Research Focus

Key Achievements

Top Papers

1. 1
   Tracking of Fingertips and Centers of Palm Using KINECT

   201 citations · 2011
2. 2
   Real-Time Robotic Hand Control Using Hand Gestures

   116 citations · 2010
3. 3
   A Survey on Hand Gesture Recognition in Context of Soft Computing

   61 citations · 2010
4. 4
   Tracking of Fingertips and Centres of Palm using KINECT

   33 citations · 2013
5. 5
   Intelligent Approaches to interact with Machines using Hand Gesture Recognition in Natural way: A Survey

   31 citations · 2011
6. 6
   A Vision based Geometrical Method to find Fingers Positions in Real Time Hand Gesture Recognition

   26 citations · 2012
7. 7
   Bent fingers’ angle calculation using supervised ANN to control electro-mechanical robotic hand

   19 citations · 2012
8. 8
   A Vision-Based Method to Find Fingertips in a Closed Hand

   17 citations · 2012
9. 9
   A Vision based Real Time System to Control Remote Robotic Hand Fingers

   14 citations · 2011
10. 10
    Real-Time BCI System Design to Control Arduino Based Speed Controllable Robot Using EEG

    11 citations · 2018

Key Collaborators

Contact & Links