125 research outputs found

    Research on a modifeied RANSAC and its applications to ellipse detection from a static image and motion detection from active stereo video sequences

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    制度:新 ; 報告番号:甲3091号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2010/2/24 ; 早大学位記番号:新535

    Motion Estimation from Disparity Images

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    A new method for 3D rigid motion estimation from stereo is proposed in this paper. The appealing feature of this method is that it directly uses the disparity images obtained from stereo matching. We assume that the stereo rig has parallel cameras and show, in that case, the geometric and topological properties of the disparity images. Then we introduce a rigid transformation (called d-motion) that maps two disparity images of a rigidly moving object. We show how it is related to the Euclidean rigid motion and a motion estimation algorithm is derived. We show with experiments that our approach is simple and more accurate than standard approaches

    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

    The compositional character of visual correspondence

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    Given two images of a scene, the problem of finding a map relating the points in the two images is known as the correspondence problem. Stereo correspondence is a special case in which corresponding points lie on the same row in the two images; optical flow is the general case. In this thesis, we argue that correspondence is inextricably linked to other problems such as depth segmentation, occlusion detection and shape estimation, and cannot be solved in isolation without solving each of these problems concurrently within a compositional framework. We first demonstrate the relationship between correspondence and segmentation in a world devoid of shape, and propose an algorithm based on connected components which solves these two problems simultaneously by matching image pixels. Occlusions are found by using the uniqueness constraint, which forces one pixel in the first image to match exactly one pixel in the second image. Shape is then introduced into the picture, and it is revealed that a horizontally slanted surface is sampled differently by the two cameras of a stereo pair, creating images of different width. In this scenario, we show that pixel matching must be replaced by interval matching, to allow intervals of different width in the two images to correspond. A new interval uniqueness constraint is proposed to detect occlusions. Vertical slant is shown to have a qualitatively different character than horizontal slant, requiring the role of vertical consistency constraints based on non-horizontal edges. Complexities which arise in optical flow estimation in the presence of slant are also examined. For greater robustness and flexibility, the algorithm based on connected components is generalized into a diffusion-like process, which allows the use of new local matching metrics which we have developed in order to create contrast invariant and noise resistant correspondence algorithms. Ultimately, it is shown that temporal information can be used to assign correspondences to occluded areas, which also yields ordinal depth information about the scene, even in the presence of independently moving objects. This information can be used for motion segmentation to detect new types of independently moving objects, which are missed by state-of-the-art methods
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