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.
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.
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.
This paper deals with an important task within forensic science - the automatic comparison of bullets for the purpose of firearm identification. Bullets bear groove-shaped marks that can be thought of as a kind of `fi...
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This paper deals with an important task within forensic science - the automatic comparison of bullets for the purpose of firearm identification. Bullets bear groove-shaped marks that can be thought of as a kind of `fingerprint' of the firearm on their circumferential surface. To accomplish the comparison task, mainly the fine grooves on the bullet surface are of interest. The presented approach is based on an automatic extraction of a `signature' describing the relevant marks. To enable a reliable feature extraction, high-quality images of the bullets are obtained. After a preprocessing step, a model-based abstraction is accomplished by adaptively projecting the image intensities of relevant grooves along their course. The resulting one-dimensional signals are not only very compact, they also have proven to provide a faithful representation of the surface information originating from the rifling of the firearm. However, an additional signal processing step is needed to separate those signal components describing the system parameters from the interesting individual marks. The performance of the methodology presented is demonstrated and quantitatively assessed with an image database of real bullets. It is shown that with our methods, the efficiency of an automatic identification of firearms can be dramatically increased.
In 1990, Mount Holyoke College began an Artificial Intelligence project centered around a mobile robot the students have named `Susan B.' One of the research threads in this project is what has been called the `Wh...
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In 1990, Mount Holyoke College began an Artificial Intelligence project centered around a mobile robot the students have named `Susan B.' One of the research threads in this project is what has been called the `Where am I?' problem, namely, the study of how to determine the robot's location using computervision. This paper describes our current approach to this problem. The environment for this work, a portion of the interior of a science building, is represented as a semantic network. This network, the `locale network', represents 3D entities, their shape and color, and relationships between them. The challenge is to use the information in color images from the robot's TV camera to identify in which of the 3D entities (room, in this case) the robot is located. This approach is based on an analysis of the color and relationship between regions in the images via a guided search of the local network. The focus of this paper is on the computervision portion of this process: color representation, the region analysis, and color matching. The color matching was inspired by Edwin Land's Retinex Theory of color constancy but depends on internal color representations to achieve constancy, rather than relying only on information in the image. Image region analysis is a Brice-Fennema process extended to work with color. This paper describes our representations and these modifications and describes experiments that show these methods to be robust under various lighting conditions.
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.
This paper describes an algorithm for the automatic segmentation and representation of surface structures and non-uniformities in an industrial setting. The automatic image processing and analysis algorithm is develop...
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This paper describes an algorithm for the automatic segmentation and representation of surface structures and non-uniformities in an industrial setting. The automatic image processing and analysis algorithm is developed as part of a complete on-line web characterization system of a papermaking process at the wet end. The goal is to: (1) link certain types of structures on the surface of the web to known machine parameter values, and (2) find the connection between detected structures at the beginning of the line and defects seen on the final product. Images of the pulp mixture (slurry), carried by a fast moving table, are obtained using a stroboscopic light and a CCD camera. This characterization algorithm succeeded where conventional contrast and edge detection techniques failed due to a poorly controlled environment. The images obtained have poor contrast and contain noise caused by a variety of sources. After a number of enhancement steps, conventional segmentation methods still failed to detect any structures and are consequently discarded. techniques tried include the Canny edge detector, the Sobel, Roberts, and Prewitt's filters, as well as zero crossings. The facet model algorithm, is then applied to the images with various parameter settings and is found to be successful in detecting the various topographic characteristics of the surface of the slurry. Pertinent topographic elements are retained and a filtered image computed. Carefully tailored morphological operators are then applied to detect and segment regions of interest. Those regions are then selected according to their size, elongation, and orientation. Their bounding rectangles are computed and represented. Also addressed in this paper are aspects of the real time implementation of this algorithm for on-line use. The algorithm is tested on over 500 images of slurry and is found to segment and characterize nonuniformities on all 500 images.
In this paper, a new variable resolution technique, foveate wavelet transform (FWT), is introduced to represent video frames in an effort to emulate the animate vision systems. Compared to the existing variable resolu...
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In this paper, a new variable resolution technique, foveate wavelet transform (FWT), is introduced to represent video frames in an effort to emulate the animate vision systems. Compared to the existing variable resolution techniques, the strength of the proposed scheme encompasses its flexibility and conciseness while supporting interesting behavior resembling the animate vision system. With the FWT as the representation, an efficient scheme to achieve purposive vision is developed. The foveate potential motion area is first labeled, the camera motion is then determined by following the labeled moving object. Experiments based on our computer-controlled pan-tilt-zoom camera have demonstrated its efficacy in real-time active camera control.
An new concept for visually guided manipulator control is introduced. It eliminates the need for a calibration of the manipulator as well as of the vision system and comprises an automatic adaptation to changing param...
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ISBN:
(纸本)0819434302
An new concept for visually guided manipulator control is introduced. It eliminates the need for a calibration of the manipulator as well as of the vision system and comprises an automatic adaptation to changing parameters. A key point of the concept is the achievement of a complex and elaborate desired goal by activating an appropriate sequence of rather simple elementary behaviors. Contrary to conventional stereo vision methods it uses an calibration-free camera system and allows a direct transition from image coordinates to motion control commands of a robot. By this approach, the abstract coordinate transformations have been avoided, instead, image data are used directly to control the behavior of the robot, or the interactions of the robot with physical objects. Thus, it makes knowledge of many hard-to-measure optical and mechanical system unnecessary;moreover, it lends itself to the realization of learning and adaptive robots. The concept has been successfully realized and tested in real-word experiments with an visually guided calibration-free 5 degree of freedom (DOF) manipulator involving the grasping of various objects with nearly any shape in arbitrary position (standing, lying, sloping) in the robot' 3-D work space.
An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The current use of these machines in outer space, medicine, hazardous materials, defense applications and industry is bei...
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ISBN:
(纸本)0819434302
An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The current use of these machines in outer space, medicine, hazardous materials, defense applications and industry is being pursued with vigor but little funding. In factory automation such robotics machines can improve productivity, increase product quality and improve competitiveness. The computer and the robot have both been developed during recent times. The intelligent robot combines both technologies and requires a thorough understanding and knowledge of mechatronics. In honor of the new millennium, this paper will present a discussion of futuristic trends and predictions. However, in keeping with technical tradition, a new technique for `Follow the Leader' will also be presented in the hope of it becoming a new, useful and non-obvious technique. Today's robotic machines are faster, cheaper, more repeatable, more reliable and safer. The knowledge base of inverse kinematic and dynamic solutions and intelligent controls is increasing. More attention is being given by industry to robots, vision and motion controls. New areas of usage are emerging for service robots, remote manipulators and automated guided vehicles. Economically, the robotics industry now has more than a billion-dollar market in the U.S. and is growing. Feasibility studies show decreasing costs for robots and unaudited healthy rates of return for a variety of robotic applications. However, the road from inspiration to successful application can be long and difficult, often taking decades to achieve a new product. A greater emphasis on mechatronics is needed in our universities. Certainly, more cooperation between government, industry and universities is needed to speed the development of intelligentrobots that will benefit industry and society.
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