Search results for "reconnaissance"
showing 10 items of 55 documents
Vehicle localization based on scene perception
2021
The vision-based vehicle localization task is tackled as an image-based place recognition problem in this thesis. As image representation is an important process to place recognition, we proposed place recognition methods focusing on increasing the quality of image features. First, the dynamic object removal step is proposed to remove the dynamic objects, such as vehicles and pedestrians, of an image by semantic segmentation method and restore their background information by image inpainting method. Second, reducing instead of removing the noisy information of an image is proposed. Using the image blurring method to reduce the image noise, the performance of place recognition is improved wi…
The parties free will in chosen filiation
2014
A cumbersome process combined with fewer adoptable children impedes French demands for adoption which results in the potential parents seeking solutions abroad. Resorting to optional filiation through international adoption or surrogacy leads prospective French parents or actual candidates, to enter multiple contracts. This contractualization of optional filiations has surprisingly swept across France, clashing against principles of French law calling for a protection of the personal status and capacity by keeping them out of contracts. This study on freedom of will within the process of optional filiation highlights the tension between the prospective and also the biological parents', and …
Inferring intentions through state representations in cooperative human-robot environments
2014
Humans and robots working safely and seamlessly together in a cooperative environment is one of the future goals of the robotics community. When humans and robots can work together in the same space, a whole class of tasks becomes amenable to automation, ranging from collaborative assembly to parts and material handling to delivery. Proposed standards exist for collaborative human-robot safety, but they focus on limiting the approach distances and contact forces between the human and the robot. These standards focus on reactive processes based only on current sensor readings. They do not consider future states or task-relevant information. A key enabler for human-robot safety in cooperative…
Influencer e diversità della pelle
2021
Ce travail s’appuie sur une série d’entretiens semi-directifs conduits avec des patientsatteints de nævus géant congénital (une maladie dermatologique rare) et les associationsimpliquées dans leur accompagnement psycho-social. Les résultats mettent en exerguel’importance des rencontres face-à-face et de l’appartenance à un groupe de pairs dans leprocessus d’acceptation et de normalisation de la différence corporelle. L’étude montre enoutre une segmentation des pratiques et des logiques de représentation de la rareté dansles différentes arènes. L’espace associatif, en ligne et hors ligne, transpose la logique de lacoopération et le renforcement de l’expertise des usagers du système sanitaire…
Recognition of emotional states by visual facial analysis and machine learning
2018
In face-to-face settings, an act of communication includes verbal and emotional expressions. From observation, diagnosis and identification of the individual's emotional state, the interlocutor will undertake actions that would influence the quality of the communication. In this regard, we suggest to improve the way that the individuals perceive their exchanges by proposing to enrich the textual computer-mediated communication by emotions felt by the collaborators. To do this, we propose to integrate a real time emotions recognition system in a platform “Moodle”, to extract them from the analysis of facial expressions of the distant learner in collaborative activities. There are three steps…
Contribution à la caractérisation de la mémoire des aliments
2008
Memory plays a fundamental role in the acquisition of food likes and dislikes. As a consequence, a better understanding food memory will contribute to a better understanding food choice and behavior. This work sets out several experiments based on a common recognition paradigm: during a first session, participants are exposed to the food to be remembered (target) under conditions ensuring incidental learning. After a certain retention interval, participants are asked to recognize the target among a set of distractors with a flavor and/or a texture slightly different from the target. In line with previous works on food memory, three main results emerged from this work. First, participants of…
3D shape recognition and matching for intelligent computer vision systems
2018
This thesis concerns recognition and matching of 3D shapes for intelligent computer vision systems. It describes two main contributions to this domain. The first contribution is an implementation of a new shape descriptor built on the basis of the spectral geometry of the Laplace-Beltrami operator; we propose an Advanced Global Point Signature (AGPS). This descriptor exploits the intrinsic structure of the object and organizes its information in an efficient way. In addition, AGPS is extremely compact since only a few eigenpairs were necessary to obtain an accurate shape description. The second contribution is an improvement of the wave kernel signature; we propose an optimized wave kernel …
Automatic recognition of tree species from 3D point clouds of forest plots
2014
The objective of the thesis is the automatic recognition of tree species from Terrestrial LiDAR data. This information is essential for forest inventory. As an answer, we propose different recognition methods based on the 3D geometric texture of the bark.These methods use the following processing steps: a preprocessing step, a segmentation step, a feature extraction step and a final classification step. They are based on the 3D data or on depth images built from 3D point clouds of tree trunks using a reference surface.We have investigated and tested several segmentation approaches on depth images representing the geometric texture of the bark. These approaches have the disadvantages of over…
Image-based detection and classification of allergenic pollen
2015
The correct classification of airborne pollen is relevant for medical treatment of allergies, and the regular manual process is costly and time consuming. An automatic processing would increase considerably the potential of pollen counting. Modern computer vision techniques enable the detection of discriminant pollen characteristics. In this thesis, a set of relevant image-based features for the recognition of top allergenic pollen taxa is proposed and analyzed. The foundation of our proposal is the evaluation of groups of features that can properly describe pollen in terms of shape, texture, size and apertures. The features are extracted on typical brightfield microscope images that enable…
Spectral interest points and texture extraction and fusion for identification, control and security
2018
Biometrics is an emerging technology that proposes new methods of control, identification and security. Biometric systems are often subject to risks. Face recognition is popular and several existing approaches use images in the visible spectrum. These traditional systems operating in the visible spectrum suffer from several limitations due to changes in lighting, poses and facial expressions. The methodology presented in this thesis is based on multispectral facial recognition using infrared and visible imaging, to improve the performance of facial recognition and to overcome the deficiencies of the visible spectrum. The multispectral images used in this study are obtained by fusion of visi…