1,721,034 research outputs found

    Predictive image compression for interactive remote visualization

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    The standard way of remotely visualizing 3D models is by first downloading them to the user's computer, and then rendering them. This approach is plagued by many problems which can be overcome by moving the rendering at server's side and by essentially turning interactive visualization into the transmission of user's prompted images. How to effectively compress the rendered views which need to be transmitted to the client is a fundamental issue within this remote visualization scenario. This work presents a predictive compression scheme for remote visualization based on image based rendering. Its experimental performance is discussed with respect to the use of JPEG and JPEG2000 within it

    Estimation of Two-Dimensional Affine Transformations Through Polar Curve Matching and Its Application to Image Mosaicking and Remote Sensing Data Registration

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    This paper presents a new and effective method for estimating two-dimensional affine transformations and its application to image registration. The method is based on matching polar curves obtained from the radial projections of the image energies, defined as the squared magnitudes of their Fourier transforms. Such matching is formulated as a simple minimization problem whose optimal solution is found with the Levenberg-Marquardt algorithm. The analysis of affine transformations in the frequency domain exploits the well-known property whereby the translational displacement in this domain can be factored out and separately estimated through phase correlation after the four remaining degrees of freedom of the affine warping have been determined. Another important contribution of this paper, emphasized through one example of image mosaicking and one example of remote sensing image registration, consists in showing that affine motion can be accurately estimated by applying our algorithm to the shapes of macrofeatures extracted from the images to register. The excellent performance of the algorithm is also shown through a synthetic example of motion estimation and its comparison with another standard registration technique

    Automatic 3-D Modeling of Textured Cultural Heritage

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    A widespread use of three-dimensional (3-D) models in cultural heritage application requires low cost equipment and technically simple modeling procedures. In this context, methods for automatic 3-D modeling of textured objects will play a central role. Such methods need fully automatic techniques for 3-D views registration and for the removal of texture artifacts. This paper proposes a contribution in this direction based on image processing approaches. The proposed procedure is very robust and simple. It does not require special equipment or skill in order to make textured 3-D models. The results of this paper, originally conceived to address the costs issues of cultural heritage modeling, can be profitably exploited also in other modeling applications

    3D scanning of cultural heritage with consumer depth cameras

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    Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate

    A New Super Resolution Technique for Range Data

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    Current Time-of-Flight matrix sensors allow for the acquisition of range maps, i.e. surface data, at video rate. This possibility is rather intriguing in light of its applications to 3D video and general motion capture. Unfortunately the resolution of the range maps acquired by such devices is quite limited specially if compared with standard color cameras. This makes highly desirable methods for improving the resolution of range maps. The characteristics of range data are completely different from those of images since geometry and light intensity are physically different quantities, therefore methods suited to image interpolation do not perform well with range data. This work presents an original interpolation technique that exploits side information from a standard color camera to increase the resolution of range maps and demonstrates its performance
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