Showing papers by "Mongi A. Abidi published in 2001"

Surface matching by 3D point's fingerprint

Abstract: This paper proposes a new efficient surface representation method for the application of surface matching. We generate a feature carrier for the surface point, which is a set of 2D contours that are the projection of geodesic circles onto the tangent plane. The carrier is named point's fingerprint because its pattern is similar to human fingerprint and discriminating for each point. Each point's fingerprint carries the information of the normal variation along geodesic circles. Corresponding points on surfaces from different views are found by comparing fingerprints of the points. This representation scheme includes more local geometry information than some previous works that only use one contour as the feature carrier. It is not histogram based so that it is able to carry more features to improve comparison accuracy. To speed up the matching, we use a novel candidate point selection method based on the shape irregularity of the projected local geodesic circle. The point's fingerprint is successfully used to register both synthetic and real 2 1/2 data.

Robust crease detection and curvature estimation of piecewise smooth surfaces from triangle mesh approximations using normal voting

Abstract: In this paper, we describe a robust method for the estimation of curvature on a triangle mesh, where this mesh is a discrete approximation of a piecewise smooth surface. The proposed method avoids the computationally expensive process of surface fitting and instead employs normal voting to achieve robust results. This method detects crease discontinuities on the surface to improve estimates near those creases. Using a voting scheme, the algorithm estimates both principal curvatures and principal directions for smooth patches. The entire process requires one user parameter-the voting neighborhood size, which is a function of sampling density, feature size, and measurement noise. We present results for both synthetic and real data and compare these results to an existing algorithm developed by Taubin (1995).

Finding objects in a 3D environment by combining distance measurement and color indexing

Abstract: A new method is presented for the localization and recognition of three-dimensional objects using color information. In the first processing step, we estimate depth information by either applying a chromatic block matching method to color stereo images or acquiring a range image from a laser scanner. Second, the computed depth maps are segmented to distinguish between the image background and the objects that should be recognized. Assuming that the segmented regions represent single objects in the three-dimensional scene, feature vectors are generated based on color histograms. The Euclidean distance is used as well as the scalar product to measure the similarity between the feature vectors computed from the color image and the feature vectors stored in a database.

Adaptive regularized noise smoothing of dense range image using directional Laplacian operators

Abstract: Noise smoothing is very important method in early vision. Recently, many signals such as an intensity image and a range image are widely used in 3D reconstruction, but the observed data are corrupted by many different sources of noise and often need to be preprocessed before further applications. This research proposes a novel adaptive regularized noise smoothing of dense range image using directional Laplacian operators. In general, dense range data includes heavy noise such as Gaussian noise and impulsive noise. Although the existing regularized noise smoothing algorithm can easily smooth Gaussian noise, impulsive noise is not easy to remove from observed range data. In addition, in order to recover the problem such as artifacts on edge region in the conventional regularized noise smoothing of range data, the second smoothness constraint is applied through minimizing the difference between the median filtered data and original data. As a result, the proposed algorithm can effectively remove the noise of dense range data with directional edge preserving.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Adaptive regularized image interpolation using data fusion and steerable constraints

Abstract: This paper presents an adaptive regularized image interpolation algorithm from blurred and noisy low resolution image sequence, which is developed in a general framework based on data fusion. This framework can preserve the high frequency components along the edge orientation in a restored high resolution image frame. This multiframe image interpolation algorithm is composed of two levels of fusion algorithm. One is to obtain enhanced low resolution images as an input data of the adaptive regularized image interpolation based on data fusion. The other one is to construct the adaptive fusion algorithm based on regularized image interpolation using steerable orientation analysis. In order to apply the regularization approach to the interpolation procedure, we first present an observation model of low resolution video formation system. Based on the observation model, we can have an interpolated image which minimizes both residual between the high resolution and the interpolated images with a prior constraints. In addition, by combining spatially adaptive constraints, directional high frequency components are preserved with efficiently suppressed noise. In the experimental results, interpolated images using the conventional algorithms are shown to compare the conventional algorithms with the proposed adaptive fusion based algorithm. Experimental results show that the proposed algorithm has the advantage of preserving directional high frequency components and suppressing undesirable artifacts such as noise.

Superquadrics-based object representation of complex scenes from range images

Abstract: This paper investigates the superquadrics-based object representation of complex scenes from range images. The issues on how the recover-and-select algorithm is incorporated to handle complex scenes containing background and multiple occluded objects are addressed respectively. For images containing backgrounds, the raw image is first coarsely segmented using the scan-line grouping technique. An area threshold is then taken to remove the backgrounds while keeping all the objects. After this pre-segmentation, the recover-and-select algorithm is applied to recover superquadric (SQ) models. For images containing multiple occluded objects, a circle-view strategy is taken to recover complete SQ models from range images in multiple views. First, a view path is planned as a circle around the objects, on which images are taken approximately every 45 degrees. Next, SQ models are recovered from each single-view range image. Finally, the SQ models from multiple views are registered and integrated. These approaches are tested on synthetic range images. Experimental results show that accurate and complete SQ models are recovered from complex scenes using our strategies. Moreover, the approach handling background problems is insensitive to the pre-segmentation error.

Gate-to-gate automated video tracking and location

Abstract: An automated gate-to-gate, airport, video tracking system is proposed and simulated using a virtual threedimensional (3D) scale model of the airport’s main concourse. The proposed research interactively combines two state-of-the-art technologies: (i) video analysis and processing and (ii) 3D visualization and simulation. The video tracking algorithm, which is realized by technology (i), has been developed with emphasis on seamless handover of a moving object using multiple cameras. The simulation environment was created based on Knoxville’s McGhee-Tyson airport using Envision software by Deneb.

Efficient part-based 3d object representation from single viewpoint range image

Abstract: This paper addresses the problem of representing 3D objects for the purpose of recognition from single viewpoint range data by using hierarchical surface and volumetric descriptions. We assumed that our target 3D objects are composed of convex volumetric primitive parts and can be modeled by superquadrics, which are composed together in a solid constructive modeling manner using union operation. For the volumetric description, we used a modified superquadric-based recover-and-select segmentation paradigm which takes input as a 3D range image. We segmented and decomposed the input object into several parts because superquadrics can be recovered directly from range data without considering any other geometric models. For each decomposed volumetric superquadric part, we calculate both surface normals and curvatures to describe surface type and surface relationships for the next recognition level. The proposed system has been tested on both synthetic and real range images, and the related experimental results are presented.

Integration of multiple range and intensity image pairs using a volumetric method to create textured three-dimensional models

Abstract: We present a volumetric approach to three-dimensional (3D) object modeling that differs from previous techniques in that both object texture and geometry are considered in the reconstruc- tion process. The motivation for the research is the simulation of a thermal tire inspection station. Integrating 3D geometry information with two-dimensional thermal images permits the thermal informa- tion to be displayed as a texture map on the tire structure, enhanc- ing analysis capabilities. Additionally, constructing the tire geometry during the inspection process allows the tire to be examined for structural defects that might be missed if the thermal data were textured onto a predefined model. Experimental results demonstrate the efficacy of the proposed approach and quantitative experiments indicate that the volumetric integration technique compares favor- ably to a state-of-the-art, mesh-based integration approach in terms of geometrical accuracy. Future research goals are also noted.