We classify 3d aerial LidAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, height variation, normal variation, Li...
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ISBN:
(纸本)9780769528250
We classify 3d aerial LidAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, height variation, normal variation, LidAR return intensity, and image intensity. We also use only LidAR-derived features to organize the data into three classes (the road and grass classes are merged). We have implemented and experimented with several variations of the SVM algorithm with soft-margin classification to allow for the noise in the data. We have applied our results to classify aerial LidAR data collected over approximately 8 square miles. We visualize the classification results along with the associated confidence using a variation of the SVM algorithm producing probabilistic classifications. We observe that the results are stable and robust. We compare the results against the ground truth and obtain higher than 90% accuracy and convincing visual results.
This paper presents a novel object recognition approach based on range images. due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions...
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ISBN:
(纸本)9780769528250
This paper presents a novel object recognition approach based on range images. due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions are good sources of information for object recognition. We propose a complete object recognition system, based on a 3d laser scanner reliable contour extraction with floor interpretation, feature extraction using a new, fast Eigen-CSS method, and a supervised learning algorithm. The recognition system was successfully tested on range images acquired with a mobile robot, and the results are compared to standard techniques, i.e., Geometric features, Hu and Zernike moments, the Border Signature method and the Angular Radial Transformation. An evaluation using the receiver operating characteristic analysis completes this paper The Eigen-CSS method has proved to be comparable in detection performance to the top competitors, yet faster than the best one by an order of magnitude in feature extraction time.
We propose a multiview tracking method for rigid objects. Assuming that a part of the object is visible in at least two cameras, a partial 3d model is reconstructed in terms of a collection of small 3d planar patches ...
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ISBN:
(纸本)9780769528250
We propose a multiview tracking method for rigid objects. Assuming that a part of the object is visible in at least two cameras, a partial 3d model is reconstructed in terms of a collection of small 3d planar patches of arbitrary topology. The 3d representation, recovered fully automatically, allows to formulate tracking as gradient minimization in pose (translation, rotation) space. As the object moves, the 3d model is incrementally updated. A virtuous circle emerges: tracking enables composition of the partial 3d model, the 3d model facilitates and robustifies the multiview tracking. We demonstrate experimentally that the interleaved track-and-reconstruct approach successfully tracks a 360 degrees turn-around and a wide range of motions. Monocular tracking is also possible after the model is constructed. Using more cameras, however significantly increases stability in critical poses and moves. We demonstrate how to exploit the 3d model to increases stability in the presence of uneven and/or changing illumination.
Utilization of an acoustic camera for range measurements is a significant advantage for 3-d shape recovery of underwater targets by opti-acoustic stereo imaging, where the associated epipolar geometry of visual and ac...
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ISBN:
(纸本)9780769528250
Utilization of an acoustic camera for range measurements is a significant advantage for 3-d shape recovery of underwater targets by opti-acoustic stereo imaging, where the associated epipolar geometry of visual and acoustic image correspondences is described in terms of conic sections and trigonometric functions. In this paper, we propose and analyze a number of methods based on direct and indirect approaches that provide insight on the merits of the new imaging and3-d object reconstruction paradigm. We have devised certain indirect methods, built on a regularization formulation, to first compute from noisy correspondences maximum likelihood estimates that satisfy the epipolar geometry. The 3-d target points can then be determined from a number of closed-form solutions applied to these ML estimates. An alternative direct approach is also presented for 3-d reocnstruction directly from noisy correspondences. Computer simulations verify consistency between the analytical and experimental reconstruction SNRs - the criterion applied in performance assessment of these various solutions.
Vanishing points are valuable in many vision tasks such as orientation estimation, pose recovery and3d reconstruction from a single image. Many methods have been proposed to address the problem, however, a consistent...
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ISBN:
(纸本)9780769528250
Vanishing points are valuable in many vision tasks such as orientation estimation, pose recovery and3d reconstruction from a single image. Many methods have been proposed to address the problem, however, a consistent framework to quantitatively analyze the stability and accuracy of vanishing point estimation is still absent. This paper proposes a new concept, vanishing hull, which solves the problem. Given an edge error model, the range of a true edge can be modeled using a fan region. The intersection of all these fan regions is a convex hull, which is called vanishing hull. A vanishing hull gives the region of a true vanishing point, and its distribution determines the probability of the vanishing point. The expectation of the vanishing hull is the optimal solution of the vanishing point, its variance defines the accuracy of the estimation, and its shape determines the stability of the vanishing point. Hence, we can quantitatively analyze the stability and accuracy of the vanishing point estimation using vanishing hull. Simulation results show that our method is significantly better than one state-of-the-art technique, and real data results are also promising.
In this paper, we propose a visual hull algorithm, which guarantees a correct construction even in the presence of partial occlusion, while "correct" here means that the real shape is located inside the visu...
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ISBN:
(纸本)9780769528250
In this paper, we propose a visual hull algorithm, which guarantees a correct construction even in the presence of partial occlusion, while "correct" here means that the real shape is located inside the visual hull. The algorithm is based on a new idea of the "extended silhouette ", which requires the silhouette from background subtraction and the "occlusion mask" of the same view. In order to prepare the occlusion mask, we also propose a novel concept of "effective boundary" of moving foreground objects in a video obtained from a static camera. The accumulation of the effective boundary through time automatically gives robust occluder boundaries. We theoretically prove that our algorithm deterministically computes the tightest, correct visual hull in the presence of occlusion. Both synthetic and real examples are given as a demonstration of the correctness of the algorithm. Finally we analyze that this new algorithm is still within the time complexity of the traditional method.
This paper addresses the problem of camera self-calibration, bundle adjustment and3d reconstruction from line segments in two images of poorly-textured indoor scenes. First, we generate line segment correspondences, ...
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ISBN:
(纸本)9780769528250
This paper addresses the problem of camera self-calibration, bundle adjustment and3d reconstruction from line segments in two images of poorly-textured indoor scenes. First, we generate line segment correspondences, using an extended version of our previously proposed matching scheme. The first main contribution is a new method to identify polyhedral junctions resulting from the intersections of the line segments. At the same time, the images are segmented into planar polygons. This is done using an algorithm based on a Binary Space Partitioning (BSP) tree. The junctions are matched end points of the detected line segments and hence can be used to obtain the epipolar geometry. The essential matrix is considered for metric camera calibration. For better stability, the second main contribution consists in a bundle adjustment on the line segments and the camera parameters that reduces the number of unknowns by a maximum flow algorithm. Finally, a piecewise-planar 3d reconstruction is computed based on the segmentation of the BSP tree. The system's performance is tested on some challenging examples.
We present a registration framework based on feature points of anatomical 3d shapes represented in the point clouddomain. Anatomical information is utilized throughout the complete registration process. The surfaces,...
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ISBN:
(纸本)9780769528250
We present a registration framework based on feature points of anatomical 3d shapes represented in the point clouddomain. Anatomical information is utilized throughout the complete registration process. The surfaces, which in this paper are ear impression models, are considered to be similar in the way that they possess the same anatomical regions but with varying geometry. First, in a shape analysis step, features of important anatomical regions (such as canal, aperture, and concha) are extracted automatically. Next these features are used in ordinary differential equutions that update rigid registration parameters between two sets of feature points. For refinement of the results, the GCP algorithm is applied. Through our experiments, we demonstrate our technique's success in surface registration through registration of key anatomical regions of human ear impressions. Furthermore, we show that the proposed method achieves higher accuracy and faster performance than the standard GCP registration algorithm.
Shape from silhouette methods are extensively used to model dynamic and non-rigid objects using binary foreground-background images. Since the problem of reconstructing shapes from silhouettes is ambiguous, a number o...
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ISBN:
(纸本)9780769528250
Shape from silhouette methods are extensively used to model dynamic and non-rigid objects using binary foreground-background images. Since the problem of reconstructing shapes from silhouettes is ambiguous, a number of solutions exist and several approaches only consider the one with a maximal volume, called the visual hull. However, the visual hull is not always a good approximation of shapes, in particular when observing smooth surfaces with few cameras. In this paper, we consider instead a class of solutions to the silhouette reconstruction problem that we call visual shapes. Such a class includes the visual hull, but also better approximations of the observed shapes which can take into account local assumptions such as smoothness, among others. Our contributions with respect to existing works is first to identify silhouette consistent shapes different from the visual hull, and second to give a practical way to estimate such shapes in real time. Experiments on various sets of data including human body silhouettes are shown to illustrate the principle and the interests of visual shapes.
This paper introduces a feature based method for the fast generation of sparse 3d point clouds from multiple images with known pose. We extract sub-pixel edge elements (2d position plus associated orientation) and use...
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ISBN:
(纸本)9780769528250
This paper introduces a feature based method for the fast generation of sparse 3d point clouds from multiple images with known pose. We extract sub-pixel edge elements (2d position plus associated orientation) and use a space sweeping scheme to compute the accurate 3d location of these edge features. Our approach relies mainly on the geometric properties of the extracted primitives and incorporates a robust uncertainty estimation to detect outliers. Epipolar constraints between views are used to narrow down the search space of potential candidates in the images. In order to improve the efficiency of spatial queries, for detecting edgels lying close to an epipolar line, we utilise a pairwise stereo rectification scheme. The detection and verification of tentative hypotheses is carried out in 3d-space, thus allowing to perform an event driven search mode. An uncertainty measure that models the location inaccuracies in the feature extraction process and errors introduced in the camera pose estimation stage allows to assign a likelihood value to each hypothesis. Optionally an image-based similarity measure can be used to verify the 3d hypotheses and to identify false positives. We perform experiments on a synthetic data set and on several real datasets. The results indicate that the proposed method yields accurate measurements on depth discontinuities and thus represents a complementary technique to standarddense matching approaches.
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