Search results for " Software"
showing 10 items of 1178 documents
Visual knowledge processing in computer-assisted radiology: A consultation system
1992
This paper presents Visual Heuristics, a consultation system for diagnosis based on thorax radiograph recording. Visual Heuristics uses both prototypical representations of physiological and pathological states and reasoning aimed to infer conclusions from pathological or physiological conditions, establishing correspondences between pathological or physiological states and semantic descriptions of images. Images are assembled with groups of descriptors that guide the recognition process, achieving the possibility of comparisons with real images on the basis of 'expected' images. The system may be employed to generate a dynamic atlas that does not contain proper images, but generates them.
An improvement of NFC-SEC with signed exchanges for an e-prescription-based application
2013
International audience; In the context of an aging population, drug intake can be a potential source of errors leading to death in some cases. Almost all of these errors are unintentional and come from incorrect prescriptions, unsuitable dosages for the patient or incompatibility with other treatments. To limit these risks which are especially important in the elderly or pre-dependency, we propose a secure system for drug treatment through the NFC (Near Field Communication) contact-less communication technology. The proposed system provides security mechanisms such as integrity, authentication, encryption and non-repudiation. To ensure this security, an extension of the international standa…
Tracking Hands in Interaction with Objects: A Review
2017
Markerless vision-based 3D hand motion tracking is a key and popular component for interaction studies in many domains such as virtual reality and natural human-computer interfaces. While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the environment or the other articulated human body parts. Employing contextual information about the surrounding environment (e.g. the shape, the texture, and the posture of the object in the hand) can remarkably constrain the tracking problem. The goal of this survey is to develop an up-to-date taxonomy of existing vision-based hand tracking m…
GPU-Based Occlusion Minimisation for Optimal Placement of Multiple 3D Cameras
2020
This paper presents a fast GPU-based solution to the 3D occlusion detection problem and the 3D camera placement optimisation problem. Occlusion detection is incorporated into the optimisation problem to return near-optimal positions for 3D cameras in environments containing occluding objects, which maximises the volume that is visible to the cameras. In addition, the authors’ previous work on 3D sensor placement optimisation is extended to include a model for a pyramid-shaped viewing frustum and to take the camera’s pose into account when computing the optimal position.
Seam-Based Edge Blending for Multi-Projection Systems
2016
Perceptual seamlessness of large-scale tiled displays is still a challenge. One way to avoid Bezel effects from contiguous displays is to blend superimposed parts of the image over the edges. This work proposes a new approach for edge blending. It is based on intensity edge blending adapted on the seam description of the image content. The main advantage of this method is to reduce visual artifacts thanks to context adaptation and smooth transitions. We evaluate the quality of the method with a perceptual experiment where it is compared with state-of-the-art methods. The new method shows most improvement in low frequency areas compared to the other techniques. This method can be inserted in…
Efficient Skin Detection under Severe Illumination Changes and Shadows
2011
International audience; This paper presents an efficient method for human skin color detection with a mobile platform. The proposed method is based on modeling the skin distribution in a log-chromaticity color space which shows good invariance properties to changing illumination. The method is easy to implement and can cope with the requirements of real-world tasks such as illumination variations, shadows and moving camera. Extensive experiments show the good performance of the proposed method and its robustness against abrupt changes of illumination and shadows.
A convolutional neural network framework for blind mesh visual quality assessment
2017
In this paper, we propose a new method for blind mesh visual quality assessment using a deep learning approach. To do this, we first extract visual representative features by computing locally curvature and dihedral angles from each distorted mesh. Then, we determine from these features a set of 2D patches which are learned to a convolutional neural network (CNN). The network consists of two convolutional layers with two max-pooling layers. Then, a multilayer perceptron (MLP) with two fully connected layers is integrated to summarize the learned representation into an output node. With this network structure, feature learning and regression are used to predict the quality score of a given d…
Towards Advanced Visualisation Techniques in Case
1999
The complexity of information systems has resulted in more sophisticated CASE tools which integrate multifaceted design information using metamodeling and hypertext technologies. A designer can use this vast amount of tightly coupled information efficiently only if it is presented based on his needs and cognitive capabilities. In this paper we discuss how representations in CASE can be improved using advanced visualisation techniques.
BioImageXD - Free Microscopy Image Processing Software
2008
Extended abstract of a paper presented at Microscopy and Microanalysis 2008 in Albuquerque, New Mexico, USA, August 3 – August 7, 2008
CrowdVAS-Net: A Deep-CNN Based Framework to Detect Abnormal Crowd-Motion Behavior in Videos for Predicting Crowd Disaster
2019
With the increased occurrences of crowd disasters like human stampedes, crowd management and their safety during mass gathering events like concerts, congregation or political rally, etc., are vital tasks for the security personnel. In this paper, we propose a framework named as CrowdVAS-Net for crowd-motion analysis that considers velocity, acceleration and saliency features in the video frames of a moving crowd. CrowdVAS-Net relies on a deep convolutional neural network (DCNN) for extracting motion and appearance feature representations from the video frames that help us in classifying the crowd-motion behavior as abnormal or normal from a short video clip. These feature representations a…