Djamal Merad

TL;DR: A photogrammetry-based approach for deep-sea underwater surveys conducted from a submarine and guided by knowledge-representation combined with a logical approach (ontology) is presented.

TL;DR: An approach for a deep-sea survey based on photogrammetry using a remotely operated underwater vehicle (ROV) gives real-time results, sufficient for piloting the ROV from the surface vessel and ensuring a uniform coverage of the site, as well as recording high-definition images using an onboard computer that will later provide a survey with millimetric precision.

TL;DR: An overview of the multi-camera tracking of objects is proposed which summarizes and classifies the most used existing methods.

TL;DR: This work aims to better understand the purchasing behavior of customers by analyzing their movements in a densely-populated sales area by using a re-identification strategy based on segmenting detected individuals into head, torso, and legs in addition to the classification of their appearances into front and back poses.

TL;DR: An investigation to find a pre-processing method of underwater images that do not require a priori knowledge of the scene in order to increase the repeatability of SIFT and SURF descriptors and a method to compute distances which will be less costly in terms of execution time for finding corresponding points.