Papers

2

Total Citations

35

H-Index

2

About

Siddhartha Chandra’s research lies at the intersection of computer vision, assistive robotics, and human–robot interaction, with a focus on enabling intelligent mobility solutions for elderly and disabled populations. His major contributions center on developing vision-based systems that allow robots to perceive and interpret human movement in real time. In his highly cited 2015 work, “Accurate Human-Limb Segmentation in RGB-D Images for Intelligent Mobility Assistance Robots,” Chandra introduced robust segmentation techniques that allow assistive robots to identify and track human limbs in cluttered environments—a critical step for safe, responsive robotic guidance. His 2016 follow-up, “Human Joint Angle Estimation and Gesture Recognition for Assistive Robotic Vision,” advanced this line of research by enabling precise joint-angle estimation and gesture recognition, empowering robots to understand user intent and respond appropriately. Together, these papers have garnered over 35 citations, reflecting their influence in the assistive robotics community. Chandra’s work directly addresses the mobility challenges faced by aging populations, aiming to restore independence and quality of life through intelligent, perceptive robotic systems. His contributions are foundational for the next generation of mobility assistance robots that can safely and intuitively collaborate with human users.

Research Focus

Key Achievements

2
H-Index
2
Papers
35
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Accurate Human-Limb Segmentation in RGB-D Images for Intelligent Mobility Assistance Robots
18 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Institut national de recherche en sciences et technologies du numérique, École Centrale Paris

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago