Search results for "Reconnaissance"
showing 10 items of 55 documents
Customer data collection infrastructure and Customer Experience Management:The SAQ Case Study
2017
Channel integration makes Customer Experience Management more complex and requires from retailers a regeneration of their value proposition. A longitudinal case study reveal a hierarchical sequence of operant resource triad: cultural mindsets, strategic directions for designing value propositions, and a dynamic system of capabilities for continually renewing customer experiences. The implementation of a customer data collection infrastructure, the adoption of an iterative and sequential innovation process, and the mobilization of cross-functional and multidisciplinary project teams, will help develop the firm’s dynamic system of capabilities.
Localisation visuelle basée sur la reconnaissance du lieu dans les environnements changeants
2017
In many applications, it is crucial that a robot or vehicle localizes itself within the world especially for autonomous navigation and driving. The goal of this thesis is to improve place recognition performance for visual localization in changing environment. The approach is as follows: in off-line phase, geo-referenced images of each location are acquired, features are extracted and saved. While in the on-line phase, the vehicle localizes itself by identifying a previously-visited location through image or sequence retrieving. However, visual localization is challenging due to drastic appearance and illumination changes caused by weather conditions or seasonal changing. This thesis addres…
Le rôle de l'aidant et sa reconnaissance
2014
International audience
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…
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…
Skeleton-Based Multiview Reconstruction
2016
International audience; The advantage of skeleton-based 3D reconstruction is to completely generate a single 3D object from well chosen views. Having numerous views is necessary for a reliable reconstruction but projections of skeletons lead to different topologies. We reconstruct 3D objects with curved medial axis (whose topology is a tree) from the perspective skeletons on an arbitrary number of calibrated acquisitions. The main contribution is to estimate the 3D skeleton, from multiple images: its topology is chosen as the closest to those of the perspective skeletons on the set of images, which means that the number of topology changes to map the 3D skeleton topology to topologies on im…
Contribution à l’apprentissage de représentation de données à base de graphes avec application à la catégorisation d’images
2020
Graph-based Manifold Learning algorithms are regarded as a powerful technique for feature extraction and dimensionality reduction in Pattern Recogniton, Computer Vision and Machine Learning fields. These algorithms utilize sample information contained in the item-item similarity and weighted matrix to reveal the intrinstic geometric structure of manifold. It exhibits the low dimensional structure in the high dimensional data. This motivates me to develop Graph-based Manifold Learning techniques on Pattern Recognition, specially, application to image categorization. The experimental datasets of thesis correspond to several categories of public image datasets such as face datasets, indoor and…
De l’oubli à la reconnaissance… les petites villes dans les politiques d’aménagement du territoire
2014
International audience
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 …
Weed and corn recognition using 2D and 3D data fusion
2001
National audience