In the emerging paradigm of animate vision, the visual processes are not thought of as being independent of cognitive or motor processing, but as an integrated system within the context of visual behavior. Intimate co...
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In the emerging paradigm of animate vision, the visual processes are not thought of as being independent of cognitive or motor processing, but as an integrated system within the context of visual behavior. Intimate coupling of sensory and motor systems have found to improve significantly the performance of behavior based vision systems. In order to study active vision systems one requires sensory-motor systems. Designing, building, and operating such a test bed is a challenging task. In this paper we describe the status of on-going work in developing a sensory-motor robotic system, R2H, with ten degrees of freedoms (DOF) for research in active vision. To complement the R2H system a Graphical Simulation and Animation (GSA) environment is also developed. The objective of building the GSA system is to create a comprehensive design tool to design and study the behavior of active systems and their interactions with the environment. GSA system aids the researchers to develop high performance and reliable software and hardware in a most effective manner. The GSA environment integrates sensing and motor actions and features complete kinematic simulation of the R2H system, it's sensors and it's workspace. With the aid of the GSA environment a Depth from Focus (DFF), Depth from Vergence, and Depth from Stereo modules are implemented and tested. The power and usefulness of the GSA system as a research tool is demonstrated by acquiring and analyzing images in the real and virtual worlds using the same software implemented and tested in the virtual world.
This paper presents a Radon transform-based approach to the detection of ship wakes in Synthetic Aperture Radar (SAR) images, The key element of this technique is a localization of the Radon transform, whereby the int...
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This paper presents a Radon transform-based approach to the detection of ship wakes in Synthetic Aperture Radar (SAR) images, The key element of this technique is a localization of the Radon transform, whereby the intensity integration is performed over short line segments rather than across the entire image. A linear feature detection algorithm, which utilizes this localized Radon transform, is then developed, In this algorithm, referred to as the feature space line detector (FSLD) algorithm, the transform space is subjected to processing which server to isolate and locate the response of linear features and suppress the responses of false alarms, This algorithm is tested on both synthetic images corrupted by various levels of Weibull multiplicative noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions,
A necessary goal in the calibration of any instrument is an indication of how well the particular device performs. In the specific case where a camera system is used in the process of three-dimensional reconstruction ...
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A necessary goal in the calibration of any instrument is an indication of how well the particular device performs. In the specific case where a camera system is used in the process of three-dimensional reconstruction or stereopsis, geometric measures of the accuracy, precision, and repeatability of 3-D point measurements give a quantitative evaluation of the success of that algorithm. This paper presents an experimental performance analysis of a traditional calibration algorithm as applied to the problem of three-dimensional vision. The study begins with an analysis of the algorithm in a single camera or monocular system. Monocular analysis concludes with a derivation of error boundaries under different. geometric constraints. Showing how this residual error propagates from the component monocular systems into a three-dimensional reconstruction, a binocular analysis derives the desired performance monitors. The paper concludes with a geometric interpretation of the results.
Present day robot systems are manufactured to perform within industry accepted tolerances. However, to use such systems for tasks requiring high precision, various methods of robot calibration are generally required. ...
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Present day robot systems are manufactured to perform within industry accepted tolerances. However, to use such systems for tasks requiring high precision, various methods of robot calibration are generally required. These procedures can improve the accuracy of a robot within a small volume of the robot's workspace. The objective of this paper is to demonstrate the use of a single camera 3D computervision system as a position sensor in order to perform robot calibration. A vision feedback scheme, termed vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation are actually sensed instead of calculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires a large number of iterations in order to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of a robot can be drastically improved. In addition, the vision system can also be used to determine the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work with an IBM Electric Drive Robot (EDR) and the proposed vision system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively.
We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficien...
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We present an integrated methodology that can be used to extract the depth from a sequence of images. The method combines the ability of stereo processing to acquire highly accurate depth measurements and the efficiency of spatial and temporal gradient analysis. As a result of this integration, depth measurements of a high quality are obtained at a speed approximately ten-times higher than that of stereo processing. Without any a priori information of the locations of the points in the scene, the correspondence problem in stereo processing is computationally expensive. In our approach, we use the spatial and temporal gradient analysis, which has been shown to provide the depth with a high efficiency but limited accuracy, to guide the stereo matching process. Experiments for lateral and axial camera translations have acquired depth results with a mean error of less than 3 percent.
This paper highlights a ranging sensor that can be calibrated at standoffs of 1 to 3 feet with a depth of field of /spl ap/1 ft. Tests at a 16" standoff have produced a 0.004 inch standard deviation in height mea...
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This paper highlights a ranging sensor that can be calibrated at standoffs of 1 to 3 feet with a depth of field of /spl ap/1 ft. Tests at a 16" standoff have produced a 0.004 inch standard deviation in height measurement errors. The data density and field of view are programmable. The sensor is positioned robotically, allowing it to provide accurate, shed-range measurements prior to manipulation tasks. The sensor head is relatively inexpensive (/spl ap/$10 k) and is designed for in situ calibration. This approach is intended to allow replacement components to be installed, calibrated, and validated without decontamination. Calibration, validation and data acquisition are all designed to be performed remotely and in a highly automated fashion. These in situ features of the design are targeted for the interest of industry with the aim of producing a sensor having a longer lifetime and a lower maintenance cost.
A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is u...
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A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The minimum noise and correlation energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 Hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation.
This paper develops and demonstrates a new computational framework for an accurate, robust, and efficient stereo approach. In multi-primitive hierarchical (MPH) computational model, stereo analysis is performed in mul...
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This paper develops and demonstrates a new computational framework for an accurate, robust, and efficient stereo approach. In multi-primitive hierarchical (MPH) computational model, stereo analysis is performed in multiple stages, incorporating multiple primitives, utilizing a hierarchical control strategy. The MPH stereo system consists of three integrated subsystems: region-based analysis module;linear edge segment-based analysis module;and edgel-based stereo analysis module. Results of stereo analysis at higher levels of the hierarchy are used for guidance at the lower levels. The MPH stereo system does not overly rely on one type of primitive and therefore will reliably work on a wide range of scenes. The MPH stereo analysis results in the generation of several disparity maps of multiple abstraction. Disparity maps generated at each level can be fused to obtain an accurate and fine resolution disparity map. The MPH approach also provides the capability to selectively analyze image regions with varying detail. This provides the means for adaptively extracting range information of only sufficient resolution. Thus, a stereo system that utilizes primitives of different abstraction and a multilevel hierarchical computational strategy will be superior to a single-level, single-primitive system. Extensive experimentation is carried out on a wide array of scenes of varying complexity from two application domains to systematically evaluate the validity and performance of the MPH framework. The MPH stereo system is able to analyze images in most cases with 85% - 100% matching accuracy in under a minute of processing time and yield depth values typically within +/-2% of the actual depth.
Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize se...
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Most simulation and animation systems utilized in robotics are concerned with simulation of the robot and its environment without simulation of sensors. These systems have difficulty in handling robots that utilize sensory feedback in their operation. In this paper, a new design of an environment for simulation, animation, and visualization of sensor-driven robots is presented. As sensor technology advances, increasing numbers of robots are equipped with various types of sophisticated sensors. The main goal of creating the visualization environment is to aid the automatic robot programming and off-line programming capabilities of sensor-driven robots. The software system will help the users visualize the motion and reaction of the sensor-driven robot under their control program. Therefore, the efficiency of the software development is increased, the reliability of the software and the operation safety of the robot are ensured, and the cost of new software development is reduced. Conventional computer-graphics-based robot simulation and animation software packages lack of capabilities for robot sensing simulation. This paper describes a system designed to overcome this deficiency.
Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. We present a new computational framework for motion perception. Our methodology considers spatio...
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Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. We present a new computational framework for motion perception. Our methodology considers spatiotemporal frequency (STF) domain analysis to extract the optical flow information. First, we show that a sequence of image frames can be used to extract the motion parameters for the different regions in a dynamic scene using the basic Fourier transform properties in the STF analysis approach. A detailed analytical description of this model to interchangably extract motion and depth parameters and results to highlight their salient properties are presented.< >
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