Search results for "Computer Vision and Pattern Recognition"
showing 10 items of 997 documents
Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection
2014
Item does not contain fulltext Cervical artery dissection (CeAD), a mural hematoma in a carotid or vertebral artery, is a major cause of ischemic stroke in young adults although relatively uncommon in the general population (incidence of 2.6/100,000 per year). Minor cervical traumas, infection, migraine and hypertension are putative risk factors, and inverse associations with obesity and hypercholesterolemia are described. No confirmed genetic susceptibility factors have been identified using candidate gene approaches. We performed genome-wide association studies (GWAS) in 1,393 CeAD cases and 14,416 controls. The rs9349379[G] allele (PHACTR1) was associated with lower CeAD risk (odds ratio…
Audiovisual Integration of Time-to-Contact Information for Approaching Objects.
2018
Previous studies of time-to-collision (TTC) judgments of approaching objects focused on effectiveness of visual TTC information in the optical expansion pattern (e.g., visual tau, disparity). Fewer studies examined effectiveness of auditory TTC information in the pattern of increasing intensity (auditory tau), or measured integration of auditory and visual TTC information. Here, participants judged TTC of an approaching object presented in the visual or auditory modality, or both concurrently. TTC information provided by the modalities was jittered slightly against each other, so that auditory and visual TTC were not perfectly correlated. A psychophysical reverse correlation approach was us…
A new design of H ∞ filtering for continuous-time Markovian jump systems with time-varying delay and partially accessible mode information
2013
In this paper, the delay-dependent H"~ filtering problem for a class of continuous-time Markovian jump linear systems with time-varying delay and partially accessible mode information is investigated by an indirect approach. The generality lies in that the systems under consideration are subject to a Markov stochastic process with exactly known and partially unknown transition rates. By utilizing the model transformation idea, an input-output approach is employed to transform the time-delayed filtering error system into a feedback interconnection formulation. Invoking the results from the scaled small gain theorem, an improved version of bounded real lemma is obtained based on a Markovian L…
Convolutional Neural Networks for Multispectral Image Cloud Masking
2020
Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.
Short baseline line matching for central imaging systems
2012
We develop a generic line matching method especially applicable to omnidirectional images taken from constructed scenes with short baseline motion where the motion of the imaging system between two views is mainly an arbitrary rotation and the translation of the camera between two views with respect to its distance to the imaged scene is negligible. We start by studying the relationship between images of lines on unitary sphere followed by proposing a simple algorithm for simultaneously matching vanishing points and lines. The developed algorithm is very simple, yet it works on images captured by all types of central imaging systems, including perspective, fish-eye and catadioptric images. …
A new minimum spanning tree-based method for shape description and matching working in Discrete Cosine space
2009
In this article, a new minimum spanning tree-based method for shape description and matching is proposed. Its properties are checked through the problem of graphical symbols recognition. Recognition invariance in front shift and multi-oriented noisy objects was studied in the context of small and low resolution binary images. The approach seems to have many desirable properties, even if the construction of graphs induces an expensive algorithmic cost. In order to reduce time computing, an alternative solution based on image compression concepts is provided. The recognition is realized in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discuss…
Towards a real-time 3D shape reconstruction using a structured light system
2005
This paper deals with 3D shape reconstruction using a structured light system (SLS) which projects a matrix of laser rays onto the scene to be analyzed. The intrinsic problem of such a system is the correspondence problem solving, which in this particular case amounts to matching up the imaged spots and the originating laser rays. In this paper, we propose a method for automatically obtaining configurations of the system (COS) (i.e. the relative positions of the camera, laser projector, and measuring scene) that permit to achieve a direct and unambiguous correspondence. After, we propose a splitting cell algorithm, which efficiently performs a real-time correspondence procedure. Experimenta…
Real Time Stereo Matching Using Two Step Zero-Mean SAD and Dynamic Programing
2018
Dense depth map extraction is a dynamic research field in a computer vision that tries to recover three-dimensional information from a stereo image pair. A large variety of algorithms has been developed. The local methods based on block matching that are prevalent due to the linear computational complexity and easy implementation. This local cost is used on global methods as graph cut and dynamic programming in order to reduce sensitivity to local to occlusion and uniform texture. This paper proposes a new method for matching images based on a two-stage of block matching as local cost function and dynamic programming as energy optimization approach. In our work introduce the two stage of th…
A stochastic shape and orientation model for fibres with an application to carbon nanotubes
2012
Methods are introduced for analysing the shape and orientation of planar fibres from greyscale images of fibrous systems. The sequence of image processing techniques needed for segmentation of fibres is described. The identified fibres were interpreted as deformed line segments for which two shape and two orientation parameters are estimated by the maximum likelihood method. The methods introduced are shown to perform quite well for simulated systems of deformed line segments with known properties. They were applied to TEM images of carbon nanotubes embedded in polycarbonate.
Oil whip-induced wear in journal bearings
2014
Published version of an article in the journal: International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-014-5805-8 This paper investigates the effect of oil whirl and oil whip in fluid film radial bearings due to possible metallic contact. The degree of metallic contact and thereby wear and tear between rotating shafts and bearing bushes is assessed by measuring electric currents through the oil film. The current as well as the voltage varied in accordance with the contact ratio between the shaft and bush in the fluid film radial bearing. The gauge signal thus indicates the degree of metallic contact based on the thi…