Djalma Lucio

Instituto Nacional de Matemática Pura e Aplicada, Pontifícia Universidade Católica do Rio de Janeiro

Papers

Total Citations

218

H-Index

About

Djalma Lucio is a leading researcher in computer vision and graphics, with a particular focus on depth sensing and human pose estimation. His pioneering work on consumer-grade RGB-D cameras, exemplified by his highly cited 2012 paper "Kinect and RGBD Images: Challenges and Applications" (212 citations), established foundational methods for integrating geometric and visual data. This research opened new frontiers in applications ranging from motion capture to medical analysis, demonstrating how accessible depth sensors could transform human-computer interaction. More recently, Lucio has advanced the field of human pose understanding with his 2020 work on "A lightweight 2D Pose Machine with attention enhancement" (6 citations), introducing efficient neural architectures that enable machines to interpret human movement in real-time. His contributions are particularly valuable for robotics, posture monitoring, and animation, where computational efficiency is critical. By bridging the gap between theoretical computer vision and practical deployment, Lucio's research continues to shape how machines perceive and interact with human motion, making sophisticated analysis accessible for real-world applications.