El Houssine Bouyakhf
Mohammed V University, Département Mathématiques et Informatique Appliquées
Papers
6
Total Citations
40
H-Index
4
About
El Houssine Bouyakhf is a leading researcher in computer vision and robotics, with a focus on 3D object recognition, human-robot interaction, and indoor environment perception. His work bridges deep learning and geometric data, notably through the use of Deep Belief Networks for classifying indoor scenes from global visual features and for recognizing 3D objects from point clouds—a critical capability for applications in robotics, aerospace, and manufacturing. Bouyakhf has also advanced robotic grasping by developing real-time object categorization techniques using visual bag-of-words and Support Vector Machines, enabling robots to identify and manipulate objects efficiently. In human-robot interaction, he introduced a depth-based approach for 3D dynamic gesture recognition using Kinect sensors, enhancing natural communication with machines. His contributions extend to omnidirectional vision, where he proposed novel methods for human detection in spherical images. With over 40 citations across his most-cited works, Bouyakhf’s research has had a tangible impact on autonomous systems and assistive robotics, making him a key figure in the integration of perception and action in intelligent machines.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4A Depth-based Approach for 3D Dynamic Gesture Recognition4 citations · 2015
- 5
- 6New approach for human detection in spherical images4 citations · 2016