Search results for "Computer vision"

showing 10 items of 2353 documents

Estimation de mouvement d'un drone à partir d'un capteur stéréo hybride

2011

Motion and velocity are two of the most important parameters to be known for an Unmanned Aerial Vehicle (UAV) especially during critical maneuvers such as landing or steady flight. In this paper, we present mixed stereoscopic vision system made of a fish-eye camera and a perspective camera for motion estimation. Contrary to classical stereoscopic systems based on feature matching between cameras, we propose an algorithm which tracks and exploits points in each camera independently. The omnidirectional view estimates the orientation of the motion while the perspective view contribute to estimate the scale of the translation and brings accuracy. By fusing points tracked in each camera and kno…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Extraction et analyse automatiques des sinus de Valsalva à partir de séquences IRM

2011

MRI appears to be particularly attractive for the study of the Sinuses of Valsalva (SV), however there is no global consensus on their suitable measurements. In this paper, we propose a new method to automatically evaluate the SV from cine-MRI in a cross-sectional orientation. It consists in the extraction of the shape, the detection of relevant points (commissures, cusps and the centre of the SV), the measure of associated distances and in a classification of the SV as bicuspid or tricuspid. Our method was tested on 23 patient examinations and radii calculations were compared with manual processing. The classification of the valve as tricuspid or bicuspid was correct for all the cases. Mor…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Numérisation 3D intelligente : deux algorithmes automatiques et progressifs

2011

This paper presents two methods for the digitization of 3D objects without prior knowledge on their shape. The first method is based on the bounding box of the object during the acquisition steps. The second method is a combination of two concepts : the Mass Vector Chains (MVC) to define the orientation of the scanned part and the Mesurability Matrix to determine the coverage rate for each view point. Tests with simulated objects were performed and results of digitization are provided.

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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View planning algorithms for fully automatic 3D acquisition of unknown objects

2013

International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel method called Orientation, Angle and Covering (OAC). The proposed method is based on a combination of two concepts: the Mass Vector Chains (MVC) and the Measurability Matrix. The MVC allows to define the global orientation of the scanned part. All of the view points are sorted using an orientation criterion to define a first set of candidates for the Next Best View (NBV). The Measurability Matrix allows to determine the coverage rate for each candidate. The covering criterion leads to reduce the number of view points of the fir…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Reconstruction monoculaire 3D de scènes agronomiques

2011

To go further in the analysis of parameters (infection rate, yield, leaf area...) of an agronomic scene, the contribution of three-dimensional information using 3D acquisition of such a scene is a relevant solution. In this paper, we propose adapting the "Shape From Focus" method to the macroscopic domain, and we clarify the reasons for this choice.

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Line Matching across Catadioptric Images under Short-Baseline Motion

2008

International audience; Line matching across catadioptric images using line intersections with focus on short baseline motion of the imaging system is proposed. The relationship between images of constructing lines of an intersection on unitary sphere is studied and angle consistency and antipodal consistency are introduced as two useful properties which can be employed to find putative intersections correspondence and remove the outliers. The necessary equations for adapting boundary of a rectangular patch to the geometry of the catadioptric images are also derived and a standard correlation is used for measuring similarities of the intersections. Experimental results on both synthetic and…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Visualisation d'images spectrales : une méthode basée sur la perception humaine

2011

We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer color-matching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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3D Scanning of specular and diffuse metallic surfaces using an infrared technique

2012

International audience; For the past two decades, the need for 3D Scanning of industrial objects has increased significantly. Therefore, many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non-cooperative surfaces, such as transparent or specular surfaces. To address highly reflective metallic surfaces, we propose the extension of a technique that was originally dedicated to glass objects. In contrast to conventional active triangulation techniques that measure the reflection of visible radiation, we measure the thermal emission of a surface, which is locally heated by a laser source. Considering the thermop…

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Complex Networks and Their Applications

2014

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
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Mirror-based matching of catadioptric images

2009

International audience

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]ComputingMilieux_MISCELLANEOUS
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