New approach for human detection in spherical images
- Resource Type
- Conference
- Authors
- Boui, Marouane; Hadj-Abdelkader, Hicham; Ababsa, Fakhr-Eddine; Bouyakhf, El Houssine
- Source
- 2016 IEEE International Conference on Image Processing (ICIP) Image Processing (ICIP), 2016 IEEE International Conference on. :604-608 Sep, 2016
- Subject
- Signal Processing and Analysis
Databases
Cameras
Measurement
Adaptation models
Training
Geometry
Robot vision systems
Omnidirectional camera
HOG
Human detection
Spherical images
- Language
- ISSN
- 2381-8549
Omnidirectional cameras are commonly used in computer vision and robotics. Their main advantage is their wide field of view which allows them to acquire a 360 degree view of the scene with only one sensor and a single shot. However, few studies have investigated the human detection problem using this kind of cameras. In this paper, we propose to extend the conventional approach for human detection in perspective images and based on Histogram of Oriented Gradients (HOG) apdapted to spherical images is used for this issue. Our approach uses the Riemannian manifolds in order to adapt the gradient in the omnidirectional images. Several experiments have been done using INRIA image database; the results show that adapting detection and image database to the geometry of omnidirectional camera allows a robust detection, and significantly increases the performances.