This paper addresses the problem of architecture optimization, when implementing an image matching primitive in reconfigurable circuits (Xilinx FPGA, for example). Circuit spatial organization is optimized in terms of...
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This paper addresses the problem of architecture optimization, when implementing an image matching primitive in reconfigurable circuits (Xilinx FPGA, for example). Circuit spatial organization is optimized in terms of processing time, and circuit volume, in order to suit well for real time on board applications. This optimized adaptive spatial and scalable organization of the μPD circuit dedicated to image matching reduces by one order the spatial and temporal performance (compared to a sequential implementation), without altering the quality of matching. The μPD circuit has been validated with the minimal 22 elementary cells architecture with Xilinx 4010 XL circuit working at 12 MHz and occupying 92% of the circuit CLB. It performs the pyramidal 256×256 image matching in less than 1 s.
Pose characterization refers to the unique representation of an object's pose through a set of image features. In this regard, one of the prerequisites for using visual images in representing an object's pose ...
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Pose characterization refers to the unique representation of an object's pose through a set of image features. In this regard, one of the prerequisites for using visual images in representing an object's pose is a set of view-dependant image features that is unique to a single position and orientation (pose) of the object relative to the camera. Here, we propose an enhancement to the global feature extraction method. It utilizes an active illumination that projects a set of orthogonal grid patterns on the object. The deformations of the grid pattern incident on the complex target object carries important information about the surface structure of the target. This grid-encoded image can be characterized using global descriptors. Results indicate that this illumination increases the sensitivity of the global features to changes in object pose.
We are interested in the development of an efficient computational visual system to study dynamic fluids and in this paper we present a methodology to detect patterns in flow-like images. These patterns are called in ...
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We are interested in the development of an efficient computational visual system to study dynamic fluids and in this paper we present a methodology to detect patterns in flow-like images. These patterns are called in the Dynamical Systems theory critical points or single points. This method, like other previous methodologies presented in related literature, involves four steps: estimation of flow directions;detection of critical point candidates;matching of critical points;and critical points description according to the Dynamical Systems theory. To achieve the critical point class, node, saddle or center point, we use templates to match the patterns. The last step of the method is necessary only if we wish a numerical representation of the patterns. We ran the method over several real images of some fluid flow classes and present the results.
Problem of pattern recognition can be interpreted as a problem of acceptance of optimal decision under conditions of uncertainty, caused by absence of the complete and authentic information about a recognized object a...
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Problem of pattern recognition can be interpreted as a problem of acceptance of optimal decision under conditions of uncertainty, caused by absence of the complete and authentic information about a recognized object and its features. The unique adequate (from the point of view of the system analysis) method of solving of pattern recognition problem in the conditions of uncertainty is the decision making by the whole set of available heterogeneous information, taking into account a significance and reliability of each of considered features and their interrelation. Usually the solution of pattern recognition problem is reduced to the task of minimization of distance from an image of the object up to the standard image of the class of objects. In this paper we offer and review the possible approach to generalization of the Mahalonobis metrics, based on properties of fuzzy number in L-R form. The results of the experimental comparison of the effectiveness of pattern recognition using the considered set of fuzzy features and criteria are discussed.
The purpose of this paper is to describe a high-level path planning logic, which processes the data from a vision system and an ultrasonic obstacle avoidance system and steers an autonomous mobile robot between obstac...
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The purpose of this paper is to describe a high-level path planning logic, which processes the data from a vision system and an ultrasonic obstacle avoidance system and steers an autonomous mobile robot between obstacles. The test bed was an autonomous robot built at University of Cincinnati, and this logic was tested and debugged on this machine. Attempts have already been made to incorporate fuzzy systems on a similar robot, and this paper extends them to take advantage of the robot's ZTR capability. Using the integrated vision system, the vehicle senses its location and orientation. A rotating ultrasonic sensor is used to map the location and size of possible obstacles. With these inputs the fuzzy logic controls the speed and the steering decisions of the robot. With the incorporation of this logic, it has been observed that Bearcat II has been very successful in avoiding obstacles very well. This was achieved in the Ground Robotics Competition conducted by the AUVS in June 1999, where it travelled a distance of 154 feet in a 10 ft. wide path ridden with obstacles. This logic proved to be a significant contributing factor in this feat of Bearcat II.
This paper presents a method to reduce the calculation costs of object pose measurements. They are estimated by matching L-shaped line-segments in 3-D object models with those in 2-D object images using a P3P solution...
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This paper presents a method to reduce the calculation costs of object pose measurements. They are estimated by matching L-shaped line-segments in 3-D object models with those in 2-D object images using a P3P solution. The L segments have the minimum pieces of information for the estimation, and, therefore, it produces a large amount of L segments both in the 3-D object models and in the 2-D object images, resulting in enormous correspondences, and P3P calculations. To solve the problem, we propose a strategy enabling to select fewer L segments: as an evaluation function, we utilizes an average of the estimation errors when observing the L segments from representative points on a geodesic dome. Furthermore, we deduce a useful approximate formula for L segments having various shapes.
In this paper, we describe a visual surveillance system for evaluating the audience's reaction in meeting sessions. The system, which works in real-time, can recognize and evaluate the reaction of the audience. It...
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In this paper, we describe a visual surveillance system for evaluating the audience's reaction in meeting sessions. The system, which works in real-time, can recognize and evaluate the reaction of the audience. It is mainly composed of three subsystems. The first subsystem is a face detection and head motion segmentation system which is used to detect the face from complex background and segment the head motion into different units, with each unit including different information about the audience's reaction. The second subsystem is a gesture and pose recognition system which can recognize the gestures and the poses of human head. The third subsystem is an evaluation system which is used to evaluate the reaction of the audience by using the recognition results in the second system. Our system has been tested for determining the concentration of the audience in meeting sessions and the experimental results are good.
This paper presents a robot based surface inspection application for measuring mould surfaces in foundries. The surface measuring is performed using a robot with six degrees of freedom equipped with a laser-triangulat...
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This paper presents a robot based surface inspection application for measuring mould surfaces in foundries. The surface measuring is performed using a robot with six degrees of freedom equipped with a laser-triangulation -based distance sensor. The measuring process is divided into four phases: sensor calibration, calibration of the mould location, surface inspection measurements and measurement analysis. In the sensor calibration phase, tool correction is calculated by using algorithms based on least square estimation with Newton iteration. Equations derived for calibration uncertainty estimation are verified using Monte Carlo simulations. The real covariance of sensor tool correction has been obtained with test measurements. Calibration of the mould location is based on the same estimation principle as was used in sensor calibration. Total uncertainty of the measuring system is obtained by transforming all separate uncertainties into one total uncertainty covariance. Spatial uncertainties are expressed and manipulated in the form of covariance matrices. The volume of the uncertainty ellipsoid in 3D space is calculated for each sensor calibration and mould location calibration. For comparison, the goodness of the measurement model is evaluated also by the condition number of the Jacobian matrix.
The determination of point correspondences between range images is used in computervision for range image registration and object recognition. The use of a spin image as a feature for matching has had considerable su...
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The determination of point correspondences between range images is used in computervision for range image registration and object recognition. The use of a spin image as a feature for matching has had considerable success in object recognition. However, in registration, refinement by iterative methods has been required. This paper presents a method of determining point correspondences between range images by matching localized spin-image point features, which contain information of the surface geometry in a local region surrounding the point. The technique is developed for range images which have little movement between viewpoints, and which consist of only several profiles each. The method involves fitting surface patches to the surfaces of the two successive views, creating spin-image features at a few points of each patch in one view, and determining the best match of features on the previous reference view using a localized interpolating search. The sets of corresponding points of the two successive range views are then used directly to compute the registration transformation between views. This computation effectively refines the correspondence by minimizing the residual errors. The technique is demonstrated using a pair of synthetic range views, derived from a range image of an object with a free-form surface.
An autonomous guided vehicle (AGV) is a multi-sensor mobile robot. The sensors of a multi-sensor robot system are characteristically complex and diverse. They supply observations, which are often difficult to compare ...
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An autonomous guided vehicle (AGV) is a multi-sensor mobile robot. The sensors of a multi-sensor robot system are characteristically complex and diverse. They supply observations, which are often difficult to compare or aggregate directly. To make efficient use of the sensory information, the capabilities of each sensor must be modeled to extract information from the environment. For this goal, a probability model of ultrasonic sensor (PMUS) is presented in this paper. The model provides a means of distributing decision making and integrating diverse opinions. Also, the paper illustrates that a series of performance factors affect the probability model as parameters. PMUS could be extended to other sensors as members of the multi-sensor team. Moreover, the sensor probability model explored is suitable for all multi-sensor mobile robots. It should provide a quantitative ability for analysis of sensor performance, and allow the development of robust decision procedures for integrating sensor information. The theoretical sensor model presented is a first step in understanding and expanding the performance of ultrasound systems. The significance of this paper lies in the theoretic integration of sensory information from the probabilistic point of view.
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