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In this paper, we present some powerful methods for computing multi-purpose image-based descriptors toward their exploitations in object detection and recognition applications. Image-based descriptors characterize image properties for constituting machine learning-based recognition systems. In this context, we present the principle for computing image-based descriptors using the local binary pattern (LBP) method. Such a method is multi-purpose in the sense that it can be efficiently exploited for the automated recognition of objects of varied natures (e.g., vehicles of traffic-monitoring images, cells of medical images). Then, we propose three variants of LBP, named Mean-LBP, \(\lambda \)-2RLBP, and C2R-LBP. The two latter ones use Hamming distance. Experimental results show that our method can overpass performances of discussed LBP methods notably under realistic conditions of use.

International audience; Nowadays, finding an available parking slot in urban environment is become more and more fastidious. In this paper, we present a model of car parking assistance system by particularly using camera networks. Such a system notably includes two research-related milestones, namely the visual detection and the communication of parking information. Hence, this paper presents a computer vision workflow permitting to detect available parking slots. Then, a strategy is proposed in order to optimally communicate to the drivers the locations of the detected available parking slots. Finally, experimental results and evaluations show the feasibility and the potential of the proposed model.

This paper presents a generic processing architecture as well as tools and approaches for supporting road monitoring services. More precisely, a small-scale simulator is presented for experimenting the design and the implementation of vision-based vehicular embedded systems in indoor environments, i.e. a test bench for embedded system laboratories. This simulator employs embedded electronic systems, sensors as well as hybrid communication and computational technologies. In particular, these technologies are exploited in order to produce our cooperative and real-time embedded system for enhancing road monitoring services. This type of simulator can be used for developing a variety of innovative road monitoring services based on the detection of dynamical points of interest. Notably, a system has been implemented in the case of a simulated road service to aid police agency for the recognition of wanted individuals and stolen vehicles. Experimental results show the potential of the simulator for fostering the development of a next generation of vehicular embedded system as well as for the emergence of participatory road services.

This paper presents emerging detection systems for improving the citizen security and comfort in vehicular and urban contexts. To this end, we firstly provide an overview of existing detection systems dealing with innovative citizen security and comfort functionalities based on vision technologies. Secondly, we expose two vision-based detection prototypes we developed for proposing services more specifically addressed to security agencies and to car drivers.

In this paper, we present an approach for the analysis of parking slots by exploiting urban surveillance networks. This work has been developed in a project which aims to facilitate to the car drivers the access to available car parking slots. This paper describes a framework that exploits video streams provided by urban networks of cameras. The objective is to remotely determine the occupancy status of parking slots. Besides, the paper presents a case study and a discussion about a broadcasting strategy that could be used to share the positions of identified vacant parking slots with drivers searching an available parking slot.

A vision-based and straightforward parking space surveillance system is presented. In particular, the novelty of the approach lies in the use of self-driven and direct dissimilarity computing mechanisms based on image raw brightness. Notably, the parking occupancy is estimated in real-time by applying fast computed estimators that optimize a global dissimilarity measure over slot-centered parking images. Experimental results show the operational capabilities and the efficiency of the proposed system mechanisms.

International audience; This article deals with visual cryptography. It consists of hiding a message in two key images (also called shares). The decryption of the message is obtained through human vision by superposition of the shares. In existing methods, the surface of key images is not visually pleasant and is not exploited for communicating textual or pictorial information. Presently, we propose a pictogram-based visual cryptography technique, which generates shares textured with customizable and aesthetic rendering. Moreover, robustness characteristics of this technique to the automated decoding of the secret message are presented. Experimental results show concrete personalized shares and their applicative potentials for security and creative domains.

In this paper, we propose a design for novel and experimental cloud computing systems. The proposed system aims at enhancing computational, communicational and annalistic capabilities of road navigation services by merging several independent technologies, namely vision-based embedded navigation systems, prominent Cloud Computing Systems (CCSs) and Vehicular Ad-hoc NETwork (VANET). This work presents our initial investigations by describing the design of a global generic system. The designed system has been experimented with various scenarios of video-based road services. Moreover, the associated architecture has been implemented on a small-scale simulator of an in-vehicle embedded system. The implemented architecture has been experimented in the case of a simulated road service to aid the police agency. The goal of this service is to recognize and track searched individuals and vehicles in a real-time monitoring system remotely connected to moving cars. The presented work demonstrates the potential of our system for efficiently enhancing and diversifying real-time video services in road environments.

The purpose of our work was to compare a group of patients undergoing transoral robotic surgery (TORS group) for squamous cell carcinoma of the upper aerodigestive tract and a matched group of patients undergoing conventional surgery (conventional surgery group) for the same indication.In this retrospective single-center study, 26 patients were included in each group.There were significantly fewer tracheotomies in the TORS group (p .001). The mean durations of feeding by nasogastric tube and hospitalization were shorter for the TORS group (p = .001). There was no significant difference in disease-free survival at 3 years (p = .76). Mean treatment cost was $7124 lower for the TORS group (p = .03).This comparative study shows that robotic technology can be used to treat selected squamous cell carcinomas of the upper aerodigestive tract, reducing morbidity and treatment costs while providing equivalent cancer control at 3 years.

In this paper we present a practical approach for generating an occlusion-free textured 3D map of urban facades by the synergistic use of terrestrial images, 3D point clouds and area-based information. Particularly in dense urban environments, the high presence of urban objects in front of the facades causes significant difficulties for several stages in computational building modeling. Major challenges lie on the one hand in extracting complete 3D facade quadrilateral delimitations and on the other hand in generating occlusion-free facade textures. For these reasons, we describe a straightforward approach for completing and recovering facade geometry and textures by exploiting the data complementarity of terrestrial multi-source imagery and area-based information.

Mobile Mapping Systems (MMS’s) are powerful tools for rapidly and massively collecting imagery in various environments (e.g., rural, semi-urban, urban). In particular, the data collected at terrestrial level can be exploited to complement aerial acquisitions for extending GIS databases,visualizing and modeling urban environments and studying environment morphogenesis over time. Hence, the development of mobile mapping platforms is a topic of great interest for many mapping agencies and surveying companies. Moreover, the experimental imaging systems of mapping vehicles are equipped with varied infrastructures in part resulting from the wide range of targeted applications. Determining a detailed design procedure for such imaging systems is of critical importance, and can be both arduous and time-consuming. Although commercial imaging systems can be exploited directly they are often pre-configured for specific applications. For these reasons, we propose a case study that deals with the development of an orientable and scalable imaging system. In particular, this paper focusses on the primary stage of the mechanical implementation of a multi-camera infrastructure. To this effect, we provide a design document that includes full technical specifications and drawings for creating a roof-mounted camera mast from a vehicle platform. We also provide an inventory of resources required for creating the system. As part of the design process we analyse some well-known MMS’s paying particular attention to their imaging systems. Finally, we evaluate the proposed design by creating the complete 3D mock-up of the camera system at real-scale and by simulating camera configurations from an experimental van platform. Experimental results clearly show the usefulness of this study in the design of an experimental and multi-purpose imaging system.

In this paper we present relevant results for the texturing of 3D urban facade models by exploiting the fusion of terrestrial multi-source data acquired by a Mobile Mapping System (MMS) and image inpainting. Current 3D urban facade models are often textured by using images that contain parts of urban objects that belong to the street. These urban objects represent in this case occlusions since they are located between the acquisition system and the facades. We show the potential use of georeferenced images and 3D point clouds that are acquired at street level by the MMS in generating occlusion-free facade textures. We describe a methodology for reconstructing quasi-real textures of facades that are highly occluded by wide frontal objects.

In this paper we present relevant results of a work in progress1 that deals with the texturing of 3D urban facade models by fusing terrestrial multi-source data acquired by a Mobile Mapping System (MMS). Some of current 3D urban facade models often are textured by using images that contain parts of urban objects that belong to the street. These urban objects represent in this case occlusions since they are located between the acquisition system and the facades. We show the potential use of georeferenced images and 3D point cloud that are acquired at street level by the MMS in generating occlusion-free facade textures. We describe a methodology for reconstructing texture parts of facades that are highly occluded by wide frontal objects.

In this paper we present a practical approach for generating an occlusion-free textured 3D map of urban facades by the synergistic use of terrestrial images, 3D point clouds and area-based information. Particularly in dense urban environments, the high presence of urban objects in front of the facades causes significant difficulties for several stages in computational building modeling. Major challenges lie on the one hand in extracting complete 3D facade quadrilateral delimitations and on the other hand in generating occlusion-free facade textures. For these reasons, we describe a straightforward approach for completing and recovering facade geometry and textures by exploiting the data complementarity of terrestrial multi-source imagery and area-based information.

This paper presents a pipeline in progress for generating virtual 3D model of urban street facades by fusing cadastral map with terrestrial images and laser data. A Mobile Mapping System (MMS) has been employed to massively gather georeferenced images and laser raw data at street level. Firstly, we describe the context as well as our motivation that aims at enriching the quality of the virtual urban environments. Secondly, we briefly present advanced works on 3D street facades mapping by merging the cadastral map and laser data. These works addressed the street facade plane estimation, their delimitation, and their texturing. Thirdly, we present a novel extension we are working on for extracting 3D detailed facade limits by fusing the cadastral map with laser and image data. This extension is essentially focused to the detection of fine 2D skylines from acquired high resolution facade images and to the estimation of the detailed 3D facade top boundaries. The presented work deals with datasets acquired in the city of Paris under real conditions. Advances and results show the potential of the envisaged pipeline for applications such as the visualization and the large scale navigation in virtual 3D street model.

This paper presents an approach for extracting 3D outlined planar clusters of street facades. Terrestrial laser data are acquired using a Mobile Mapping System (MMS). Mapping of street facades is of great interest in various digital mapping and robotic research topics. After a filtering step of the 3D point cloud, the dominant hypothetical facade planes are detected using an adapted Progressive Probabilistic Hough Transform (PPHT). The corresponding planar clusters are extracted using a priori geometric knowledge of street. The clusters are horizontally and vertically delimited using heuristic approaches. The adapted PPHT allows the automatic extraction of georeferenced planar clusters of facades with a fine detection of dominant facade lines and a low computation time. The adopted approach has been tested on a set of point cloud acquired in the city of Paris under real conditions. Examples and experimental results show the efficiency and the potential of the proposed approach.

The aim of this work is to develop research on 3D building modeling. In particular, the research in aerial-based 3D building reconstruction is a topic very developed since 1990. However, it is necessary to pursue the research since the actual approaches for 3D massive building reconstruction (although efficient) still encounter problems in generalization, coherency, accuracy. Besides, the recent developments of street acquisition systems such as Mobile Mapping Systems open new perspectives for improvements in building modeling in the sense that the terrestrial data (very dense and accurate) can be exploited with more performance (in comparison to the aerial investigation) to enrich the building models at facade level (e.g., geometry, texturing).Hence, aerial and terrestrial based building modeling approaches are individually proposed. At aerial level, we describe a direct and featureless approach for simple polyhedral building reconstruction from a set of calibrated aerial images. At terrestrial level, several approaches that essentially describe a 3D urban facade modeling pipeline are proposed, namely, the street point cloud segmentation and classification, the geometric modeling of urban facade and the occlusion-free facade texturing, L'objectif principal de ce travail est le développement de recherches en modélisation 3D du bâti. En particulier, la recherche en reconstruction 3D de bâtiment est un sujet très développé depuis les années 90. Malgré tout, il paraît nécessaire de poursuivre les recherches dans cet axe étant données que les approches actuelles consacrées à la reconstruction 3D de bâtiment (bien qu'efficaces) rencontrent encore des difficultés en terme de généralisation, de cohérence et de précision. Par ailleurs, les récents développements des systèmes d'acquisitions de rues tel que les systèmes de cartographie mobile ouvrent de nouvelles perspectives d'amélioration de la modélisation des bâtiments dans le sens ou les données terrestres (très précises et résolus) peuvent être exploitées avec davantage de cohérence (en comparaison à l'aérien) pour enrichir les modèles de bâtiments au niveau des façades (la géométrie, la texture).Ainsi, des approches de modélisation aériennes et terrestres sont individuellement proposées. Au niveau aérien, nous décrivons une approche directe et dépourvu d'extraction et d'assemblage de primitives géométriques en vue de la reconstruction 3D de modèles polyédriques simples de bâtiments à partir d'un jeu d'images aériennes calibrées. Au niveau terrestre, plusieurs approches qui décrivent essentiellement un pipeline pour la modélisation 3D des façades urbaines sont proposées; à savoir, la segmentation et classification de nuage de rues urbaines, la modélisation géométrique des façades urbaines et le texturage des façades urbaines comportant des occultations causées par d'autres objets du mobilier urbains