Results 11  20
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65
Outlier robust ICP for minimizing fractional RMSD
 ArXiv
, 2006
"... We describe a variation of the iterative closest point (ICP) algorithm for aligning two point sets under a set of transformations. Our algorithm is superior to previous algorithms because (1) in determining the optimal alignment, it identifies and discards likely outliers in a statistically robust m ..."
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Cited by 20 (1 self)
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We describe a variation of the iterative closest point (ICP) algorithm for aligning two point sets under a set of transformations. Our algorithm is superior to previous algorithms because (1) in determining the optimal alignment, it identifies and discards likely outliers in a statistically robust manner, and (2) it is guaranteed to converge to a locally optimal solution. To this end, we formalize a new distance measure, fractional root mean squared distance (FRMSD), which incorporates the fraction of inliers into the distance function. Our framework can easily incorporate most techniques and heuristics from modern registration algorithms. We experimentally validate our algorithm against previous techniques on 2 and 3 dimensional data exposed to a variety of outlier types. 1
Worstcase and smoothed analysis of the ICP algorithm, with an application to the kmeans method
 In Proc. of the 47th Ann. IEEE Symp. on Foundations of Computer Science (FOCS
, 2006
"... We show a worstcase lower bound and a smoothed upper bound on the number of iterations performed by the Iterative Closest Point (ICP) algorithm. First proposed by Besl and McKay, the algorithm is widely used in computational geometry where it is known for its simplicity and its observed speed. The ..."
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Cited by 20 (3 self)
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We show a worstcase lower bound and a smoothed upper bound on the number of iterations performed by the Iterative Closest Point (ICP) algorithm. First proposed by Besl and McKay, the algorithm is widely used in computational geometry where it is known for its simplicity and its observed speed. The theoretical study of ICP was initiated by Ezra, Sharir and Efrat, who bounded its worstcase running time between Ω(n log n) and O(n 2 d) d. We substantially tighten this gap by improving the lower bound to Ω(n/d) d+1. To help reconcile this bound with the algorithm’s observed speed, we also show the smoothed complexity of ICP is polynomial, independent of the dimensionality of the data. Using similar methods, we improve the best known smoothed upper bound for the popular kmeans method to n O(k) , once again independent of the dimension. 1.
Temporally Coherent Completion of Dynamic Shapes
"... We present a novel shape completion technique for creating temporally coherent watertight surfaces from realtime captured dynamic performances. Because of occlusions and low surface albedo, scanned mesh sequences typically exhibit large holes that persist over extended periods of time. Most convent ..."
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Cited by 20 (4 self)
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We present a novel shape completion technique for creating temporally coherent watertight surfaces from realtime captured dynamic performances. Because of occlusions and low surface albedo, scanned mesh sequences typically exhibit large holes that persist over extended periods of time. Most conventional dynamic shape reconstruction techniques rely on template models or assume slow deformations in the input data. Our framework sidesteps these requirements and directly initializes shape completion with topology derived from the visual hull. To seal the holes with patches that are consistent with the subject’s motion, we first minimize surface bending energies in each frame to ensure smooth transitions across hole boundaries. Temporally coherent dynamics of surface patches are obtained by unwarping all frames within a time window using accurate interframe correspondences. Aggregated surface samples are then filtered with a temporal visibility kernel that maximizes the use of nonoccluded surfaces. A key benefit of our shape completion strategy is that it does not rely on longrange correspondences or a template model. Consequently, our method does not suffer from error accumulation typically introduced by noise, large deformations, and drastic topological changes. We illustrate the effectiveness of our method on several highresolution scans of human performances captured with a stateoftheart multiview 3D acquisition system.
Matching 2.5D Scans for Face Recognition
 In: International Conference on Pattern Recognition
, 2004
"... Abstract. The performance of face recognition systems that use twodimensional images is dependent on consistent conditions such as lighting, pose, and facial appearance. We are developing a face recognition system that uses threedimensional depth information to make the system more robust to these ..."
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Abstract. The performance of face recognition systems that use twodimensional images is dependent on consistent conditions such as lighting, pose, and facial appearance. We are developing a face recognition system that uses threedimensional depth information to make the system more robust to these arbitrary conditions. We have developed a face matching system that automatically correlates points in three dimensions between two 2.5D range images of different views. A hybrid Iterative Closest Point (ICP) scheme is proposed to integrate two classical ICP algorithms for fine registration of the two scans. A robust similarity metric is defined for matching purpose. Results are provided on a preliminary database of 10 subjects (one training image per subject) containing frontal face images of neutral expression with a testing database of 63 scans that varied in pose, expression and lighting. 1.
The ThreeDimensional NormalDistributions Transform  an Efficient Representation for Registration, Surface Analysis, and Loop Detection
 ÖREBRO STUDIES IN TECHNOLOGY
, 2013
"... This dissertation is concerned with threedimensional (3D) sensing and 3D scan representation. Threedimensional records are important tools in several, quite diverse, disciplines; such as medical imaging, archaeology, and mobile robotics. In the case of mobile robotics (the discipline that is prima ..."
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Cited by 16 (6 self)
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This dissertation is concerned with threedimensional (3D) sensing and 3D scan representation. Threedimensional records are important tools in several, quite diverse, disciplines; such as medical imaging, archaeology, and mobile robotics. In the case of mobile robotics (the discipline that is primarily targeted by the present work), 3D scanning of the environment is useful in several subtasks, such as mapping, localisation, and extraction of semantic information from the robot’s environment. This dissertation proposes the normaldistributions transform, NDT, as a general 3D surface representation with applications in scan registration, localisation, loop detection, and surfacestructure analysis. Range scanners typically produce data in the form of point clouds. After applying NDT to the original discrete point samples, the scanned surface is instead represented by a piecewise smooth function with analytic first and secondorder derivatives. Such a representation has a number of attractive properties. The smooth function representation makes it possible to use standard methods
Cached kd tree search for ICP algorithms
"... The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of threedimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, kd trees have been used to accelerate the sea ..."
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Cited by 14 (1 self)
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The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of threedimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, kd trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached kd trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speedup of about 50 % as we show in an evaluation using different data sets. 1
Symmetry detection using feature lines
 Comput. Graph. Forum
, 2009
"... In this paper, we describe a new algorithm for detecting structural redundancy in geometric data sets. Our algorithm computes rigid symmetries, i.e., subsets of a surface model that reoccur several times within the model differing only by translation, rotation or mirroring. Our algorithm is based on ..."
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Cited by 12 (0 self)
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In this paper, we describe a new algorithm for detecting structural redundancy in geometric data sets. Our algorithm computes rigid symmetries, i.e., subsets of a surface model that reoccur several times within the model differing only by translation, rotation or mirroring. Our algorithm is based on matching locally coherent constellations of feature lines on the object surfaces. In comparison to previous work, the new algorithm is able to detect a large number of symmetric parts without restrictions to regular patterns or nested hierarchies. In addition, working on relevant features only leads to a strong reduction in memory and processing costs such that very large data sets can be handled. We apply the algorithm to a number of real world 3D scanner data sets, demonstrating high recognition rates for general patterns of symmetry.
Automatic registration of overlapping 3D point clouds using closest points
 Image Vision Comput
, 2006
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3D Pose Estimation and Segmentation using Specular Cues
"... We present a system for fast modelbased segmentation and 3D pose estimation of specular objects using appearance based specular features. We use observed (a) specular reflection and (b) specular flow as cues, which are matched against similar cues generated from a CAD model of the object in various ..."
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We present a system for fast modelbased segmentation and 3D pose estimation of specular objects using appearance based specular features. We use observed (a) specular reflection and (b) specular flow as cues, which are matched against similar cues generated from a CAD model of the object in various poses. We avoid estimating 3D geometry or depths, which is difficult and unreliable for specular scenes. In the first method, the environment map of the scene is utilized to generate a database containing synthesized specular reflections of the object for densely sampled 3D poses. This database is compared with captured images of the scene at run time to locate and estimate the 3D pose of the object. In the second method, specular flows are generated for dense 3D poses as illumination invariant features and are matched to the specular flow of the scene. We incorporate several practical heuristics such as use of saturated/highlight pixels for fast matching and normal selection to minimize the effects of interreflections and cluttered backgrounds. Despite its simplicity, our approach is effective in scenes with multiple specular objects, partial occlusions, interreflections, cluttered backgrounds and changes in ambient illumination. Experimental results demonstrate the effectiveness of our method for various synthetic and real objects.
The registration problem revisited: Optimal solutions from points, lines and planes
 In Conf. Computer Vision and Pattern Recognition, NewYork City
, 2006
"... In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both pointtopoint, pointtoline and pointtoplane correspondences in the optimization algorithm. T ..."
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Cited by 9 (4 self)
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In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework that allows us to use both pointtopoint, pointtoline and pointtoplane correspondences in the optimization algorithm. Traditional methods such as the iterative closest point algorithm may get trapped in local minima due to the nonconvexity of the problem, however, our approach guarantees global optimality. The approach is based on ideas from global optimization theory, in particular, convex underestimators in combination with branch and bound. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data. 1.