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In this paper, we propose a dense approach for 3D rotation estimation between spherical images, which is simultaneously able to recover the large rotations, robust under clutter and small translations. The key idea is to represent the spherical images by 3D shapes of the triangular mesh surfaces based on image intensity signal. This allows to apply the spherical harmonics representation as 3D shape...
This paper presents a novel rotation estimation approach based on 3D mesh representation of spherical images. Indeed, unit sphere is becoming a natural space for projecting images captured from the central cameras (conventional and non-conventional cameras, as omnidirectional camera) and obtaining the spherical images. The proposed method relies on representing the spherical images into a 3D space...
Since a large field of view obviously bears important advantages, the use of spherical images is becoming increasingly important in various computer vision and image processing applications. This paper presents a novel rotation estimation approach for spherical images based on 3D mesh representation of gray level intensity. Once the 3D meshes of the underlying spherical images are obtained, the 3D...
In this work, we propose real time implementation approaches of distributed Constant False Alarm Rate (CFAR) detection with noncoherent integration. The Cell Averaging (CA-CFAR) and Clutter MAP (CMAP-CFAR) detectors are employed as local detectors. The proposed architecture shows that it can be implemented with the advantages of a parallel structure and allows an important optimization of the required...
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