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Mongi A. Abidi

Researcher at University of Tennessee

Publications -  366
Citations -  7941

Mongi A. Abidi is an academic researcher from University of Tennessee. The author has contributed to research in topics: Image processing & Image segmentation. The author has an hindex of 42, co-authored 365 publications receiving 7573 citations. Previous affiliations of Mongi A. Abidi include Centre national de la recherche scientifique & Oak Ridge National Laboratory.

Papers
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Journal ArticleDOI

Point fingerprint: a new 3-D object representation scheme

TL;DR: A novel candidate point selection method based on the fingerprint irregularity is introduced and it is successfully applied to pose estimation of real range data.
Journal ArticleDOI

Heterogeneous Fusion of Omnidirectional and PTZ Cameras for Multiple Object Tracking

TL;DR: Two methods are proposed: 1) geometry and 2) homography calibration, where polynomials with automated model selection are used to approximate the camera's projection model and spatial mapping, respectively, to improve the mapping accuracy and improve flexibility in adjusting to varying system configurations.
Proceedings ArticleDOI

Triangle mesh-based edge detection and its application to surface segmentation and adaptive surface smoothing

TL;DR: A robust edge detection algorithm for triangle meshes and its applications to surface segmentation and adaptive surface smoothing is proposed and results on surfaces reconstructed from multi-view real range images are presented.
Journal ArticleDOI

Color active shape models for tracking non-rigid objects

TL;DR: This paper presents a hierarchical realization of an enhanced active shape model for color video tracking and studies the performance of both hierarchical and nonhierarchical implementations in the RGB, YUV, and HSI color spaces.
Journal ArticleDOI

Survey and analysis of multimodal sensor planning and integration for wide area surveillance

TL;DR: In this article, a survey and analysis conducted in light of these challenging requirements and constraints is presented, which involves techniques and strategies from work done in the areas of sensor fusion, sensor networks, smart sensing, Geographic Information Systems (GIS), photogrammetry, and other intelligent systems where finding optimal solutions to the placement and deployment of multimodal sensors covering a wide area is important.