J. M. H. du Buf

About

J. M. H. du Buf is a leading researcher in biologically inspired computer vision and robotics, with a focus on creating systems that mimic human visual perception for real-world interaction. His work spans object detection, pedestrian recognition, and human-robot interaction, often drawing on cortical multi-scale processing models. A major contribution is the development of a low-cost, classroom-oriented educational robotics system (24 citations), which has made robotics more accessible for learning environments. He also advanced category-level object detection with an efficient Naive Bayes approach (5 citations), offering a fast filtering alternative to traditional methods. His research on detecting indoor and outdoor stairs (27 citations) has practical applications in assistive robotics, while his work on facial expression recognition and hand gesture frameworks (5 and 3 citations) integrates biological vision principles into real-time systems. Du Buf’s impact is evident in his consistent exploration of multi-stage features for pedestrian detection (5 citations) and proto-object categorization for local gist vision (3 citations), contributing to smarter navigation and interaction in indoor environments. His biologically inspired approaches continue to influence the fields of computer vision and robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Detection of Indoor and Outdoor Stairs

   27 citations · 2013
2. 2
   A Low-Cost Classroom-Oriented Educational Robotics System

   24 citations · 2013
3. 3
   An efficient Naive Bayes approach to category-level object detection

   5 citations · 2014
4. 4
   Using Multi-Stage Features in Fast R-CNN for Pedestrian Detection

   5 citations · 2016
5. 5
   Recognition of Facial Expressions by Cortical Multi-scale Line and Edge Coding

   5 citations · 2010
6. 6
   Real-Time Object Recognition Based on Cortical Multi-scale Keypoints

   4 citations · 2013
7. 7
   A Biological and Real-Time Framework for Hand Gestures and Head Poses

   3 citations · 2013
8. 8
   Proto-object categorisation and local gist vision using low-level spatial features

   3 citations · 2015
9. 9
   Biologically Inspired Vision for Indoor Robot Navigation

   2 citations · 2014
10. 10
    Biologically Inspired Vision for Human-Robot Interaction

    2 citations · 2015

Key Collaborators

Contact & Links