Search results for " Vision"
showing 10 items of 2709 documents
Chess recognition using 3D patterned illumination camera
2021
Computer Vision has been applied to augment traditional board games such as Chess for a number of reasons. While augmented reality enhances the gaming experience, the required additional hardware (e.g. head gear) is still not widely accepted in everyday leisure activities, and therefore, camera based methods have been developed to interface the computer with the real-life chess board. However, traditional 2D camera approaches suffer from ill-defined environmental conditions (lighting, viewing angle) and are therefore severely limited in their application. To answer this issue, we have incorporated a consumer-grade depth camera based on patterned illumination. We could show that in combinati…
Deep multimodal fusion for semantic image segmentation: A survey
2021
International audience; Recent advances in deep learning have shown excellent performance in various scene understanding tasks. However, in some complex environments or under challenging conditions, it is necessary to employ multiple modalities that provide complementary information on the same scene. A variety of studies have demonstrated that deep multimodal fusion for semantic image segmentation achieves significant performance improvement. These fusion approaches take the benefits of multiple information sources and generate an optimal joint prediction automatically. This paper describes the essential background concepts of deep multimodal fusion and the relevant applications in compute…
Stereopsis assessment at multiple distances with an iPad application
2017
[EN] We present a new application for iPad for screening stereopsis at multiple distances that allows testing up to ten levels of stereoacuity at each distance. Our approach is based on a random dot stereogram viewable with anaglyph spectacles. Sixty-five subjects with no ocular diseases, wearing their habitual correction were measured at 3 m and 0.5 m. Results were compared with a standard stereoscopic test (TNO). We found not statistically significant differences between both tests, but our method achieved higher reproducibility. Applications in visual screening programs and to design and use of 3D displays, are suggested. (C) 2017 Elsevier B.V. All rights reserved.
Machine Learning Techniques for Intrusion Detection: A Comparative Analysis
2016
International audience; With the growth of internet world has transformed into a global market with all monetary and business exercises being carried online. Being the most imperative resource of the developing scene, it is the vulnerable object and hence needs to be secured from the users with dangerous personality set. Since the Internet does not have focal surveillance component, assailants once in a while, utilizing varied and advancing hacking topologies discover a path to bypass framework " s security and one such collection of assaults is Intrusion. An intrusion is a movement of breaking into the framework by compromising the security arrangements of the framework set up. The techniq…
Automated prostate gland segmentation based on an unsupervised fuzzy C-means clustering technique using multispectral T1w and T2w MR imaging
2017
Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection and delineation of prostate gland on multispectral MRI data is currently a time-expensive and operator-dependent procedure. Efficient computer-assisted segmentation approaches are not yet able to address these issues, but rather have the potential to do so. In this paper, a novel automatic prostate MR image segmentation method based on the Fuzzy C-Means (FCM) clustering algorithm, which enables multispectral T1-weighted (T1w) and T2-weighted (T…
Efficient linear fusion of partial estimators
2018
Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…
Online Multi-Person Tracking by Tracker Hierarchy
2012
Tracking-by-detection is a widely used paradigm for multi-person tracking but is affected by variations in crowd density, obstacles in the scene, varying illumination, human pose variation, scale changes, etc. We propose an improved tracking-by-detection framework for multi-person tracking where the appearance model is formulated as a template ensemble updated online given detections provided by a pedestrian detector. We employ a hierarchy of trackers to select the most effective tracking strategy and an algorithm to adapt the conditions for trackers' initialization and termination. Our formulation is online and does not require calibration information. In experiments with four pedestrian t…
Real Time Image Rotation Using Dynamic Reconfiguration
2002
Abstract Field programmable gate array (FPGA) components are widely used nowdays to implement various algorithms, such as digital filtering, in real time. The emergence of dynamically reconfigurable FPGAs made it possible to reduce the number of necessary resources to carry out an image-processing task (tasks chain). In this article, an image-processing application, image rotation, that exploits the FPGAs dynamic reconfiguration method is presented. This paper shows that the choice of an implementation, static or dynamic reconfiguration, depends on the nature of the application. A comparison is carried out between the dynamic and the static reconfiguration using two criteria: cost and perfo…
Design and calibration of an omni-RGB+D camera
2016
International audience; In this paper, we present the design of a new camera combining both predator-like and prey-like vision features. This setup provides both a spherical RGB-view and a directional depth-view of the environment. The model and calibration of the full setup are described. A few examples will be given to demonstrate the interest and the versatility of such camera for robotics and video surveillance at the oral presentation.
Dorsal Column Nuclei Neural Signal Features Permit Robust Machine-Learning of Natural Tactile- and Proprioception-Dominated Stimuli
2020
Neural prostheses enable users to effect movement through a variety of actuators by translating brain signals into movement control signals. However, to achieve more natural limb movements from these devices, the restoration of somatosensory feedback is required. We used feature-learnability, a machine-learning approach, to assess signal features for their capacity to enhance decoding performance of neural signals evoked by natural tactile and proprioceptive somatosensory stimuli, recorded from the surface of the dorsal column nuclei (DCN) in urethane-anesthetized rats. The highest performing individual feature, spike amplitude, classified somatosensory DCN signals with 70% accuracy. The hi…