Scene Interpretation in Images and Videos - Jakkoju, Chetan;Jawahar, C. V.;Krishna, Madhava
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Scene interpretation is a fundamental task in both computer vision and robotic systems. We deal with two important aspects of scene interpretation, they are scene reconstruction and scene recognition. Scene reconstruction is determining 3D positions of world points and retrieving camera poses from images. It has several applications such as virtual building editing, video augmentation; and planning and navigation in robotics. Among several approaches to modeling the scene, we deal with piecewise planar modeling due to several advantages. We propose a convex optimization based, approach for…mehr

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Produktbeschreibung
Scene interpretation is a fundamental task in both computer vision and robotic systems. We deal with two important aspects of scene interpretation, they are scene reconstruction and scene recognition. Scene reconstruction is determining 3D positions of world points and retrieving camera poses from images. It has several applications such as virtual building editing, video augmentation; and planning and navigation in robotics. Among several approaches to modeling the scene, we deal with piecewise planar modeling due to several advantages. We propose a convex optimization based, approach for piecewise planar reconstruction. Scene recognition in robotics, specifically terrain scene recognition is one of the fundamental tasks of autonomous navigation. Navigable terrains are examples of planar scenes. It has applications in various domains such as advanced driver assistance systems, remote sensing, etc. Various sensing modalities such as ladars, lasers, accelerometers, stereo cameras,or combination of them are used in literature. We propose an algorithm which is purely based on a single monocular camera.
Autorenporträt
Chetan Jakkoju obtained his MS and BTech in computer science at IIIT-H, India. He is currently working as a member of technical staff in Serial Innovations (sitpl.com A spinoff from Sarnoff). His research interests are primarily in the areas of computer vision and machine learning; and the application of computer vision to problems in robotics.