Model-based interpretation of stereo imagery of textured surfaces

We present a scheme for reliable and accurate surface reconstruction from stereoscopic images containing only fine texture and no stable high-level features. Partial shape information is used to improve surface computation: first by fitting an approximate, global, parametric model, and then by refining this model via local correspondence processes. This scheme eliminates the window size selection problem in existing area-based stereo correspondence schemes. These ideas are integrated in a practical vision system that is being used by environmental scientists to study wind erosion of bulk material such as coal ore being transported in open rail cars. Received: 14 August 1995 / Accepted: 27 May 1997     

Attributed point matching for automatic groundtruth generation

Geometric groundtruth at the character, word, and line levels is crucial for designing and evaluating optical character recognition (OCR) algorithms. Kanungo and Haralick proposed a closed-loop methodology for generating geometric groundtruth for rescanned document images. The procedure assumed that the original image and the corresponding groundtruth were available. It automatically registered the original image to the rescanned one using four corner points and then transformed the original groundtruth using the estimated registration transformation. In this paper, we present an attributed branch-and-bound algorithm for establishing the point correspondence that uses all the data points. We group the original feature points into blobs and use corners of blobs for matching. The Euclidean distance between character centroids is used as the error metric. We conducted experiments on synthetic point sets with varying layout complexity to characterize the performance of two matching algorithms. We also report results on experiments conducted using the University of Washington dataset. Finally, we show examples of application of this methodology for generating groundtruth for microfilmed and FAXed versions of the University of Washington dataset documents. Received: July 24, 2001 / Accepted: May 20, 2002     

A hybrid approach for stereo disparity computation

An alternative, hybrid approach for disparity estimation, based on the phase difference technique, is presented. The proposed technique combines the robustness of the matching method with the sub-pixel accuracy of the phase difference approach. A matching between the phases of the left and right signals is introduced in order to allow the phase difference method to work in a reduced disparity range. In this framework, a new criterion to detect signal singularities is proposed. The presented test cases show that the performance of the proposed technique in terms of accuracy and density of the disparity estimates has greatly improved. Received: 24 June 1997 / Accepted: 15 September 1998     

Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis

This paper presents an automatic multiple-scale algorithm for delineation of individual tree crowns in high spatial resolution infrared colour aerial images. The tree crown contours were identified as zero-crossings, with convex grey-level curvature, which were computed on the intensity image for each image scale. A modified centre of curvature was estimated for every edge segment pixel. For each segment, these centre points formed a swarm which was modelled as a primal sketch using an ellipse extended with the mean circle of curvature. The model described the region of the derived tree crown based on the edge segment at the current scale. The sketch was rescaled with a significance value and accumulated for a scale interval. In the accumulated sketch, a tree crown segment was grown, starting at local peaks, under the condition that it was inside the area of healthy vegetation in the aerial image and did not trespass into a neighbouring crown segment. The method was evaluated by comparison with manual delineation and with ground truth on 43 randomly selected sample plots. It was concluded that the performance of the method is almost equivalent to visual interpretation. On the average, seven out of ten tree crowns were the same. Furthermore, ground truth indicated a large number of hidden trees. The proposed technique could be used as a basic tool in forest surveys. Received: 24 June 1997 / Accepted: 28 April 1998     

A compact algorithm for rectification of stereo pairs

Abstract. We present a linear rectification algorithm for general, unconstrained stereo rigs. The algorithm takes the two perspective projection matrices of the original cameras, and computes a pair of rectifying projection matrices. It is compact (22-line MATLAB code) and easily reproducible. We report tests proving the correct behavior of our method, as well as the negligible decrease of the accuracy of 3D reconstruction performed from the rectified images directly. Received: 25 February 1999 / Accepted: 2 March 2000     

Active shape from stereo for highway inspection

Abstract. This paper describes an unsupervised algorithm for estimating the 3D profile of potholes in the highway surface, using structured illumination. Structured light is used to accelerate computation and to simplify the estimation of range. A low-resolution edge map is generated so that further processing may be focused on relevant regions of interest. Edge points in each region of interest are used to initialise open, active contour models, which are propagated and refined, via a pyramid, to a higher resolution. At each resolution, internal and external constraints are applied to a snake; the internal constraint is a smoothness function and the external one is a maximum-likelihood estimate of the grey-level response at the edge of each light stripe. Results of a provisional evaluation study indicate that this automated procedure provides estimates of pothole dimension suitable for use in a first, screening, assessment of highway condition. Received: 9 October 1998 / Accepted: 22 February 2000     

The reconstruction of dynamic 3D structure of biological objects using stereo microscope images

In this paper, we address the analysis of 3D shape and shape change in non-rigid biological objects imaged via a stereo light microscope. We propose an integrated approach for the reconstruction of 3D structure and the motion analysis for images in which only a few informative features are available. The key components of this framework are: 1) image registration using a correlation-based approach, 2) region-of-interest extraction using motion-based segmentation, and 3) stereo and motion analysis using a cooperative spatial and temporal matching process. We describe these three stages of processing and illustrate the efficacy of the proposed approach using real images of a live frog's ventricle. The reconstructed dynamic 3D structure of the ventricle is demonstrated in our experimental results, and it agrees qualitatively with the observed images of the ventricle.     

Automatic extraction of roads from aerial images based on scale space and snakes

Abstract. We propose a new approach for automatic road extraction from aerial imagery with a model and a strategy mainly based on the multi-scale detection of roads in combination with geometry-constrained edge extraction using snakes. A main advantage of our approach is, that it allows for the first time a bridging of shadows and partially occluded areas using the heavily disturbed evidence in the image. Additionally, it has only few parameters to be adjusted. The road network is constructed after extracting crossings with varying shape and topology. We show the feasibility of the approach not only by presenting reasonable results but also by evaluating them quantitatively based on ground truth. Received: 22 July 1999 / Accepted: 20 March 2000     

Registration and interactive planar segmentation for stereo images of polyhedral scenes

We introduce a two-step iterative segmentation and registration method to find coplanar surfaces among stereo images of a polyhedral environment. The novelties of this paper are: (i) to propose a user-defined initialization easing the image matching and segmentation, (ii) to incorporate color appearance and planar projection information into a Bayesian segmentation scheme, and (iii) to add consistency to the projective transformations related to the polyhedral structure of the scenes. The method utilizes an assisted Bayesian color segmentation scheme. The initial user-assisted segmentation is used to define search regions for planar homography image registration. The two reliable methods cooperate to obtain probabilities for coplanar regions with similar color information that are used to get a new segmentation by means of quadratic Markov measure fields (QMMF). We search for the best regions by iterating both steps: registration and segmentation.     

Robust classification of arbitrary object classes based on hierarchical spatial feature-matching

We present a novel approach to the robust classification of arbitrary object classes in complex, natural scenes. Starting from a re-appraisal of Marr's ‘primal sketch’, we develop an algorithm that (1) employs local orientations as the fundamental picture primitives, rather than the more usual edge locations, (2) retains and exploits the local spatial arrangement of features of different complexity in an image and (3) is hierarchically arranged so that the level of feature abstraction increases at each processing stage. The resulting, simple technique is based on the accumulation of evidence in binary channels, followed by a weighted, non-linear sum of the evidence accumulators. The steps involved in designing a template for recognizing a simple object are explained. The practical application of the algorithm is illustrated, with examples taken from a broad range of object classification problems. We discuss the performance of the algorithm and describe a hardware implementation. First successful attempts to train the algorithm, automatically, are presented. Finally, we compare our algorithm with other object classification algorithms described in the literature.     

Random perturbation models for boundary extraction sequence

Computer vision algorithms are composed of different sub-algorithms often applied in sequence. Determination of the performance of a total computer vision algorithm is possible if the performance of each of the sub-algorithm constituents is given. The performance characterization of an algorithm has to do with establishing the correspondence between the random variations and imperfections in the output data and the random variations and imperfections in the input data. In this paper we illustrate how random perturbation models can be set up for a vision algorithm sequence involving edge finding, edge linking, and gap filling. By starting with an appropriate noise model for the input data we derive random perturbation models for the output data at each stage of our example sequence. By utilizing the perturbation model for edge detector output derived, we illustrate how pixel noise can be successively propagated to derive an error model for the boundary extraction output. It is shown that the fragmentation of an ideal boundary can be described by an alternating renewal process and that the parameters of the renewal process are related to the probability of correct detection and grouping at the edge linking step. It is also shown that the characteristics of random segments generated due to gray-level noise are functions of the probability of false alarm of the edge detector. Theoretical results are validated through systematic experiments.     

The ALIVE system: wireless, full-body interaction with autonomous agents

The cumbersome nature of wired interfaces often limits the range of application of virtual environments. In this paper, we discuss the design and implementation of a novel system, called ALIVE, which allows unencumbered full-body interaction between a human participant and a rich graphical world inhabited by autonomous agents. Based on results obtained with thousands of users, the paper argues that this kind of system can provide more complex and very different experiences than traditional virtual reality systems. The ALIVE system significantly broadens the range of potential applications of virtual reality systems; in particular, the paper discusses novel applications in the area of training and teaching, entertainment, and digital assistants or interface agents. We give an overview of the methods used in the implementation of the existing ALIVE systems.     

A survey of approaches to automatic schema matching

Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component. Received: 5 February 2001 / Accepted: 6 September 2001 Published online: 21 November 2001     

Whole-body modelling of people from multiview images to populate virtual worlds

In this paper a new technique is introduced for automatically building recognisable, moving 3D models of individual people. A set of multiview colour images of a person is captured from the front, sides and back by one or more cameras. Model-based reconstruction of shape from silhouettes is used to transform a standard 3D generic humanoid model to approximate a person's shape and anatomical structure. Realistic appearance is achieved by colour texture mapping from the multiview images. The results show the reconstruction of a realistic 3D facsimile of the person suitable for animation in a virtual world. The system is inexpensive and is reliable for large variations in shape, size and clothing. This is the first approach to achieve realistic model capture for clothed people and automatic reconstruction of animated models. A commercial system based on this approach has recently been used to capture thousands of models of the general public.     

Coarse-to-fine adaptive masks for appearance matching of occluded scenes

In this paper, we discuss an appearance-matching approach to the difficult problem of interpreting color scenes containing occluded objects. We have explored the use of an iterative, coarse-to-fine sum-squared-error method that uses information from hypothesized occlusion events to perform run-time modification of scene-to-template similarity measures. These adjustments are performed by using a binary mask to adaptively exclude regions of the template image from the squared-error computation. At each iteration higher resolution scene data as well as information derived from the occluding interactions between multiple object hypotheses are used to adjust these masks. We present results which demonstrate that such a technique is reasonably robust over a large database of color test scenes containing objects at a variety of scales, and tolerates minor 3D object rotations and global illumination variations. Received: 21 November 1996 / Accepted: 14 October 1997     

Iterative model-based binarization algorithm for cheque images

Binarization of document images with poor contrast, strong noise, complex patterns, and variable modalities in the gray-scale histograms is a challenging problem. A new binarization algorithm has been developed to address this problem for personal cheque images. The main contribution of this approach is optimizing the binarization of a part of the document image that suffers from noise interference, referred to as the Target Sub-Image (TSI), using information easily extracted from another noise-free part of the same image, referred to as the Model Sub-Image (MSI). Simple spatial features extracted from MSI are used as a model for handwriting strokes. This model captures the underlying characteristics of the writing strokes, and is invariant to the handwriting style or content. This model is then utilized to guide the binarization in the TSI. Another contribution is a new technique for the structural analysis of document images, which we call “Wavelet Partial Reconstruction” (WPR). The algorithm was tested on 4,200 cheque images and the results show significant improvement in binarization quality in comparison with other well-established algorithms. Received: October 10, 2001 / Accepted: May 7, 2002 This research was supported in part by NCR and NSERC's industrial postgraduate scholarship No. 239464. A simplified version of this paper has been presented at ICDAR 2001 [3].     

Localization of spherical fruits for robotic harvesting

The orange picking robot (OPR) is a project for developing a robot that is able to harvest oranges automatically. One of the key tasks in this robotic application is to identify the fruit and to measure its location in three dimensions. This should be performed using image processing techniques which must be sufficiently robust to cope with variations in lighting conditions and a changing environment. This paper describes the image processing system developed so far to guide automatic harvesting of oranges, which here has been integrated in the first complete full-scale prototype OPR. Received: 16 April 2000 / Accepted: 19 December 2000     

Parameterization for reconstruction of 3D freeform objects from laser-scanned data based on a PDE method

Published online: 19 July 2001