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Fusion of Sonar and Optical data for fish tracking and recognition / Hicham CHABILI

Public ISBD Titre : Fusion of Sonar and Optical data for fish tracking and recognition Type de document : projet fin études Auteurs : Hicham CHABILI, Auteur Langues : Français (fre) Catégories : SDBD Mots-clés : Underwater computer vision, Sonar, Fish Detection , Sensor Fusion. Index. décimale : mast 87/18 Résumé : The ecological underwater system is continuously changing. Underwater marine life is still shrouded in mystery. Knowing it, learning about it and conserving it are an inevitable part of living all around it. In a time when various challenges are facing the marine life, the ability to see and know what is underwater and where it is located is of the utmost importance. Underwater detection and identification of species has become a prominent field at the intersection of marine studies and computer science. The use of the latest and most sophisticated captors to relay an almost perfect image of the underwater scenery, and the application of the most powerful artificial intelligence algorithms along with the incredible knowledge the marine studies offer create a multi-disciplinary research breakthrough. In this thesis, we conduct a thorough investigation of the various approaches to the issue of underwater species’ detection and identification. We specifically discuss the use of sonar techniques and video tracking techniques along with their fusion as problems to the aforementioned species’ recognition issue. To that end, we propose an approach to sonar and video fusion by exploiting fish movements in a shared timeframe. We implement and verify sonar and video techniques on different sets of data, and draw conclusions from each to determine limitations, infer learned lessons and explore future opportunities of research. Fusion of Sonar and Optical data for fish tracking and recognition [projet fin études] / Hicham CHABILI, Auteur . - [s.d.]. Langues : Français (fre) Catégories : SDBD Mots-clés : Underwater computer vision, Sonar, Fish Detection , Sensor Fusion. Index. décimale : mast 87/18 Résumé : The ecological underwater system is continuously changing. Underwater marine life is still shrouded in mystery. Knowing it, learning about it and conserving it are an inevitable part of living all around it. In a time when various challenges are facing the marine life, the ability to see and know what is underwater and where it is located is of the utmost importance. Underwater detection and identification of species has become a prominent field at the intersection of marine studies and computer science. The use of the latest and most sophisticated captors to relay an almost perfect image of the underwater scenery, and the application of the most powerful artificial intelligence algorithms along with the incredible knowledge the marine studies offer create a multi-disciplinary research breakthrough. In this thesis, we conduct a thorough investigation of the various approaches to the issue of underwater species’ detection and identification. We specifically discuss the use of sonar techniques and video tracking techniques along with their fusion as problems to the aforementioned species’ recognition issue. To that end, we propose an approach to sonar and video fusion by exploiting fish movements in a shared timeframe. We implement and verify sonar and video techniques on different sets of data, and draw conclusions from each to determine limitations, infer learned lessons and explore future opportunities of research.

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Code barre	Cote	Support	Localisation	Section	Disponibilité
mast 87/18	mast 87/18 HIC	Texte imprimé	Unité des masters	Mast/18	Disponible