222 research outputs found

    Conjugate epipole-based self-calibration of camera under circular motion

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    In this paper, we propose a new method to self-calibrate camera with constant internal parameters under circular motion. The basis of our approach is to make use of the conjugate epipoles which are related to camera positions with rotation angles satisfying the conjugate constraint. A novel circular projective reconstruction is developed for computing the conjugate epipoles robustly. It is shown that for a camera with zero skew, two turntable sequences with different camera orientations are needed, and for a general camera three sequences with different camera orientations are required. The performance of the algorithm is tested with real images.published_or_final_versio

    Relative Affine Structure: Canonical Model for 3D from 2D Geometry and Applications

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    We propose an affine framework for perspective views, captured by a single extremely simple equation based on a viewer-centered invariant we call "relative affine structure". Via a number of corollaries of our main results we show that our framework unifies previous work --- including Euclidean, projective and affine --- in a natural and simple way, and introduces new, extremely simple, algorithms for the tasks of reconstruction from multiple views, recognition by alignment, and certain image coding applications

    Direct Methods for Estimation of Structure and Motion from Three Views

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    We describe a new direct method for estimating structure and motion from image intensities of multiple views. We extend the direct methods of Horn- and-Weldon to three views. Adding the third view enables us to solve for motion, and compute a dense depth map of the scene, directly from image spatio -temporal derivatives in a linear manner without first having to find point correspondences or compute optical flow. We describe the advantages and limitations of this method which are then verified through simulation and experiments with real images

    A trifocal transfer based virtual microscope for robotic manipulation of MEMS components.

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    International audienceThe paper deals with the problem of imaging at the microscale. The trifocal transfer based novel view synthesis approach is developed and applied to the images from two photon microscopes mounted in a stereoscopic configuration and observing vertically the work scene. The final result is a lateral virtual microscope working up to 6 frames per second with a resolution up to that of the real microscopes. Visual feedback, accurate measurements and control have been performed with, showing it ability to be used for robotic manipulation of MEMS parts. Keywords: Novel view synthesis, trifocal tensor, photon microscope, microassembly, micromanipulation, MEMS

    An empirical assessment of real-time progressive stereo reconstruction

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    3D reconstruction from images, the problem of reconstructing depth from images, is one of the most well-studied problems within computer vision. In part because it is academically interesting, but also because of the significant growth in the use of 3D models. This growth can be attributed to the development of augmented reality, 3D printing and indoor mapping. Progressive stereo reconstruction is the sequential application of stereo reconstructions to reconstruct a scene. To achieve a reliable progressive stereo reconstruction a combination of best practice algorithms needs to be used. The purpose of this research is to determine the combinat ion of best practice algorithms that lead to the most accurate and efficient progressive stereo reconstruction i.e the best practice combination. In order to obtain a similarity reconstruction the in t rinsic parameters of the camera need to be known. If they are not known they are determined by capturing ten images of a checkerboard with a known calibration pattern from different angles and using the moving plane algori thm. Thereafter in order to perform a near real-time reconstruction frames are acquired and reconstructed simultaneously. For the first pair of frames keypoints are detected and matched using a best practice keypoint detection and matching algorithm. The motion of the camera between the frames is then determined by decomposing the essential matrix which is determined from the fundamental matrix, which is determined using a best practice ego-motion estimation algorithm. Finally the keypoints are reconstructed using a best practice reconstruction algorithm. For sequential frames each frame is paired with t he previous frame and keypoints are therefore only detected in the sequential frame. They are detected , matched and reconstructed in the same fashion as the first pair of frames, however to ensure that the reconstructed points are in the same scale as the points reconstructed from the first pair of frames the motion of the camera between t he frames is estimated from 3D-2D correspondences using a best practice algorithm. If the purpose of progressive reconstruction is for visualization the best practice combination algorithm for keypoint detection was found to be Speeded Up Robust Features (SURF) as it results in more reconstructed points than Scale-Invariant Feature Transform (SIFT). SIFT is however more computationally efficient and thus better suited if the number of reconstructed points does not matter, for example if the purpose of progressive reconstruction is for camera tracking. For all purposes the best practice combination algorithm for matching was found to be optical flow as it is the most efficient and for ego-motion estimation the best practice combination algorithm was found to be the 5-point algorithm as it is robust to points located on planes. This research is significant as the effects of the key steps of progressive reconstruction and the choices made at each step on the accuracy and efficiency of the reconstruction as a whole have never been studied. As a result progressive stereo reconstruction can now be performed in near real-time on a mobile device without compromising the accuracy of reconstruction

    Euclidean Structure from Uncalibrated Images

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    Visuelle Detektion unabhängig bewegter Objekte durch einen bewegten monokularen Beobachter

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    The development of a driver assistant system supporting drivers in complex intersection situations would be a major achievement for traffic safety, since many traffic accidents happen in such situations. While this is a highly complex task, which is still not accomplished, this thesis focused on one important and obligatory aspect of such systems: The visual detection of independently moving objects. Information about moving objects can, for example, be used in an attention guidance system, which is a central component of any complete intersection assistant system. The decision to base such a system on visual input had two reasons: (i) Humans gather their information to a large extent visually and (ii) cameras are inexpensive and already widely used in luxury and professional vehicles for specific applications. Mimicking the articulated human head and eyes, agile camera systems are desirable. To avoid heavy and sensitive stereo rigs, a small and lightweight monocular camera system mounted on a pan-tilt unit has been chosen as input device. In this thesis information about moving objects has been used to develop a prototype of an attention guidance system. It is based on the analysis of sequences from a single freely moving camera and on measurements from inertial sensors rigidly coupled with the camera system.Die Entwicklung eines Fahrerassistenzsystems, welches den Fahrer in komplexen Kreuzungssituationen unterstützt, wäre ein wichtiger Beitrag zur Verkehrssicherheit, da sehr viele Unfälle in solchen Situationen passieren. Dies ist eine hochgradig komplexe Aufgabe und daher liegt der Fokus dieser Arbeit auf einen wichtigen und notwendigen Aspekt solcher Systeme: Die visuelle Detektion unabhängig bewegter Objekte. Informationen über bewegte Objekte können z.B. für ein System zur Aufmerksamkeitssteuerung verwendet werden. Solch ein System ist ein integraler Bestandteil eines jeden kompletten Kreuzungsassistenzssystems. Zwei Gründe haben zu der Entscheidung geführt, das System auf visuellen Daten zu stützen: (i) Der Mensch sammelt seine Informationen zum Großteil visuell und (ii) Kameras sind zum Einen günstig und zum Anderen bereits jetzt in vielen Fahrzeugen verfügbar. Agile Kamerasysteme sind nötig um den beweglichen menschlichen Kopf zu imitieren. Die Wahl einer kleinen und leichten monokularen Kamera, die auf einer Schwenk-Neige-Einheit montiert ist, vermeidet die Verwendung von schweren und empfindlichen Stereokamerasystemen. Mit den Informationen über bewegte Objekte ist in dieser Arbeit der Prototyp eines Fahrerassistenzsystems Aufmerksamkeitssteuerung entwickelt worden. Das System basiert auf der Analyse von Bildsequenzen einer frei bewegten Kamera und auf Messungen von der mit der Kamera starr gekoppelten Inertialsensorik
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