A method for temporally integrating appearance-based body-part labelling is presented. We begin by modifying the silhouette labelling method of Ghost;that system first determines which posture best describes the perso...
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A method for temporally integrating appearance-based body-part labelling is presented. We begin by modifying the silhouette labelling method of Ghost;that system first determines which posture best describes the person currently and then uses posture-specific heuristics to generate labels for head, hands, and feet. Our approach is to assign a posture probability and then estimate body part locations for all possible postures. Next we temporally integrate these estimates by finding a best path through the posture-time lattice. A density-sampling propagation approach is used that allows us to model the multiple hypotheses resulting from consideration of different postures. We show quantitative and qualitative results where the temporal integration solution improves the instantaneous estimates. This method can be applied to any system that inherently has multiple methods of asserting instantaneous properties but from which a temporally coherent interpretation is desired.
The paper presents an approach of using algorithmic skeletons for adding data parallelism to an imageprocessing.library. The method is used for parallelizing imageprocessing.applications composed of low-level image ...
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A desktop vision system is presented for complete 3D model acquisition. It is fast, low-cost, and accurate. Partial 3D shapes and texture information are acquired from multiple viewing directions using rotational ster...
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A desktop vision system is presented for complete 3D model acquisition. It is fast, low-cost, and accurate. Partial 3D shapes and texture information are acquired from multiple viewing directions using rotational stereo and shape from focus (SFF). The resulting range images are registered to a common coordinate system and a surface representation is created for each range image. The resulting surfaces are integrated using a new algorithm named Region-of-Construction. Unlike previous approaches, the Region-of-Construction algorithm directly exploits the structure of the raw range images. The algorithm determines regions in range images corresponding to non-redundant surfaces which can be stitched along the boundaries to construct the complete 3D surface model. The algorithm is computationally efficient and less sensitive to registration error. It also has the ability to construct complete 3D models of complex objects with holes. A photo realistic 3D model is obtained by mapping texture information onto the complete surface model representing 3D shape. Experimental results for several real objects are presented.
Previous work has demonstrated that the image variations of many objects (human faces in particular) under variable lighting can be effectively modeled by low dimensional linear spaces. Basis images spanning this spac...
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Previous work has demonstrated that the image variations of many objects (human faces in particular) under variable lighting can be effectively modeled by low dimensional linear spaces. Basis images spanning this space are usually obtained in one of two ways: A large number of images of the object under different conditions is acquired, and principal component analysis (PCA) is used to estimate a subspace. Alternatively, a 3-D model (perhaps reconstructed from images) is used to render virtual images under either point sources from which a subspace is derived using PCA or more recently under diffuse synthetic lighting based on spherical harmonics. In this paper, we show that there exists a configuration of nine point light source directions such that by taking nine images of each individual under these single sources, the resulting subspace is effective at recognition under a wide range of lighting conditions. Since the subspace is generated directly from real images, potentially complex intermediate steps such as PCA and 3D reconstruction can be completely avoided;nor is it necessary to acquire large numbers of training images or physically construct complex diffuse (harmonic) light fields. We provide both theoretical and empirical results to explain why these linear spaces should be good for recognition.
In the exploration of the other planets of our solar system, images taken during a lander's descent to the surface of a planet provide a critical link between orbital images and surface images. The descent images ...
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In the exploration of the other planets of our solar system, images taken during a lander's descent to the surface of a planet provide a critical link between orbital images and surface images. The descent images not only allow us to locate the landing site in a global coordinate frame, but also provide progressively higher-resolution maps for mission planning. This paper addresses the generation of depth maps from the descent images. Our approach has two steps, motion refinement and depth recovery. During motion refinement, we use an initial motion estimate in order to avoid the intrinsic ambiguity in descending motions. The objective of the motion refinement step is to adjust the motion parameters such that the epipolar constraints are valid between adjacent frames. The depth recovery step correlates adjacent frames to match pixels for triangulation. Due to the descending motion, the conventional rectification process is replaced by a set of anti-aliasing image warpings corresponding to a set of virtual parallel planes. We demonstrate experimental results on synthetic and real descent images.
This paper presents a method for detecting building outlines using multiple aerial images. Since data-driven techniques may not be able to account for variability of building geometry and appearances, a key insight ex...
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This paper presents a method for detecting building outlines using multiple aerial images. Since data-driven techniques may not be able to account for variability of building geometry and appearances, a key insight explored in this paper is a combination of model-based data driven front end with data driven learning in the back end for increased detection accuracy. Three main components of the detection algorithm are (i) Initialization. image intensity and depth information are integrally used to efficiently detect buildings, and a robust rectilinear path finding algorithm is adopted to obtain good initial outlines. The initialization process involves the following steps: detecting location of buildings, determining the dominant orientations and knot points in the building outline and using these to fit the initial outline. (ii) Learning. A compact set of building features are defined and learned from the well-delineated buildings, and a tree-based classifier is applied to the whole region to detect any missing buildings and obtain their rough outlines. (iii) Verification and Refinement. Learned features are used to remove falsely detected buildings, and all outlines are refined by the deformation of rectilinear templates. The experiments, with improved detection rate and precise outlines, demonstrate the applicability of our algorithm.
While computer vision systems often assume simple illumination models, real-world illumination is highly complex, consisting of reflected light from every direction as well as distributed and localized primary light s...
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While computer vision systems often assume simple illumination models, real-world illumination is highly complex, consisting of reflected light from every direction as well as distributed and localized primary light sources. One can capture the illumination incident at a point in the real world from every direction photographically using a spherical illumination map. This paper illustrates, through analysis of photographically-acquired, high dynamic range. illumination maps, that real-world illumination shares many of the statistical properties of natural images. In particular, the marginal and joint wavelet coefficient distributions, directional derivative distributions, and harmonic spectra of illumination maps resemble those documented in the natural image statistics literature. However, illumination maps differ from standard photographs in that illumination maps are statistically non-stationary and may contain localized light sources that dominate their power spectra. Our work provides a foundation for statistical models of real-world illumination that may facilitate robust estimation of shape, reflectance, and illumination from images.
image-based relighting (IBL) is a technique to change the illumination of an image-based object/scene. In this paper, we define a representation called the reflected irradiance field which records the reflection from ...
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image-based relighting (IBL) is a technique to change the illumination of an image-based object/scene. In this paper, we define a representation called the reflected irradiance field which records the reflection from an object surface irradiated by a point light source that moves on a plane. This representation is dual to that of the light field. It synthesizes a novel image under a different illumination by interpolating and superimposing appropriate recorded samples. Furthermore, we study the minimum sampling problem of the reflected irradiance field, i.e., how many point light sources are needed during sampling. We find that there exists a geometry-independent bound for the sampling interval whenever the second-order derivatives of the surface BRDF and the minimum depth of the scene are bounded. This bound ensures that the error in the reconstructed image is controlled by a given tolerance, regardless of the geometry. Experiments on both synthetic and real surfaces are conducted to verify our analysis.
Accurate calculation of the three dimensional shape of an object is one of the classic research areas of computer vision. Many of the existing methods are based on surface normal estimation, and subsequent integration...
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Accurate calculation of the three dimensional shape of an object is one of the classic research areas of computer vision. Many of the existing methods are based on surface normal estimation, and subsequent integration of surface gradients. In general, these methods do not produce valid surface due to violation of surface integrability. We introduce a new method for shape reconstruction by integration of valid surface gradient maps. The essence of the new approach is in the strict enforcement of the surface integrability via belief propagation across graphical model. The graphical model is selected in such a way to extract information from underlying, possibly noisy, surface gradient estimators, utilize the surface integrability constraint, and produce the maximum a-posteriori estimate of a valid surface. We demonstrate the algorithm for two classic shape reconstruction techniques;shape-from-shading and photometric stereo. On a set of real and synthetic examples the new approach is shown to be fast and accurate, in the sense that shape can be rendered even in the presence of high levels of noise and sharp occlusion boundaries.
This paper describes a graph-spectral method for 3D surface integration. The algorithm takes as its input a 2D field of surface normal estimates, delivered, for instance, by a shape-from-shading or shape-from-texture ...
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This paper describes a graph-spectral method for 3D surface integration. The algorithm takes as its input a 2D field of surface normal estimates, delivered, for instance, by a shape-from-shading or shape-from-texture procedure. The method borrows ideas from routing theory. We exploit the well-known fact that the leading eigenvector of a Markov chain transition probability matrix is the steady-state random walk on the equivalent weighted graph. We use this property to find the minimum total curvature path through the available surface normals. To do this we construct a transition probability matrix whose elements are related to the differences in surface normal direction. By threading the surface normals together along the path specified by the magnitude order of the components of the leading eigenvector we perform surface integration. The height increments along the path are simply related to the traversed path length and the slope of the local tangent plane. The method is evaluated on data delivered by a shape-from-shading algorithm.
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