This letter proposes a novel nonlinear distortion for the unique identification of receiving room impulses in stereo acoustic echo cancellation when applying the frequency-domain adaptive filtering technique. This nonlinear distortion is effective in reducing the coherence between the two incoming audio channels and its influence on audio quality is inaudible.

This paper presents a VLSI processor for high-speed and reliable stereo matching based on adaptive window-size control of SAD(Sum of Absolute Differences) computation. To reduce its computational complexity, SADs are computed using multi-resolution images. Parallel memory access is essential for highly parallel image processing. For parallel memory access, this paper also presents an optimal memory allocation that minimizes the hardware amount under the condition of parallel memory access at specified resolutions.

This paper proposed the advantages of using a 2D/3D hybrid imagery system over the use of 3D by itself. A hybrid imagery system was created by projecting a 3D (stereo) image in between and overlapping onto two adjacent 2D images. The negative effect where 2D and 3D images overlap was studied and resolved. Then sensations subject experienced from the visual cues under the different conditions were attained. Participant's sensations while looking at the different forms of imagery on both a flat screen and a flat/inclined screen combination were then attained. The data for the 2D/3D hybrid system were compared with that attained for a 3D image system on its own (without 2D images). Results indicate that there are benefits to using a 2D/3D hybrid system over 3D by itself.

This paper presents the analysis of the stopping maneuver of the human driver by using a new three-dimensional driving simulator that uses CAVE, which provides stereoscopic immersive vision. First of all, the difference in the driving behavior between 3D and 2D virtual environments is investigated. Secondly, a GMDH is applied to the measured data in order to build a mathematical model of driving behavior. From the obtained model, it is found that the acceleration information has less importance in stopping maneuver under the 2D and 3D environments.

Our goal is to realize an extra-large stereoscopic display in the open air for use by the general public. We have developed a stereoscopic large display by use of a full-color LED panel. Although the developed display enables viewers to view the stereoscopic images without any special glasses, it is necessary for the viewers to move to stand within the viewing areas. Movements of the viewers are considered to depend on arrangements of viewing areas. The purpose of this paper is to investigate the movements of viewers who watch different designs of stereoscopic LED displays with a parallax barrier, including conventional designs to provide multiple perspective images and designs to eliminate pseudoscopic viewing areas, and evaluate the performance of different viewing areas based on the obtained paths of the viewers. We have developed a real-time measurement system of a viewer's position by use of a camera on the ceiling. We have recorded the viewing movements caused by the shift of viewing areas. It was found that the viewers moved to stand on orthoscopic viewing positions. The movements of viewers who move to find a viewing area have been recorded with different designs of stereoscopic LED displays that provide different viewing areas. We have calculated the lateral moving time of the viewers'movements. It is shown that the elimination of pseudoscopic viewing areas reduces the lateral moving time. Thus, the real-time measurement system of a viewer's position has been utilized for evaluation of performance of the different designs of stereoscopic LED displays.

In this paper, we propose two adaptive filtering schemes for Stereophonic Acoustic Echo Cancellation (SAEC), which are based on the adaptive projected subgradient method (Yamada et al., 2003). To overcome the so-called non-uniqueness problem, the schemes utilize a certain preprocessing technique which generates two different states of input signals. The first one simultaneously uses, for fast convergence, data from two states of inputs, meanwhile the other selects, for stability, data based on a simple min-max criteria. In addition to the above difference, the proposed schemes commonly enjoy (i) robustness against noise by introducing the stochastic property sets, and (ii) only linear computational complexity, since it is free from solving systems of linear equations. Numerical examples demonstrate that the proposed schemes achieve, even in noisy situations, compared with the conventional technique, (i) much faster and more stable convergence in the learning process as well as (ii) lower level mis-identification of echo paths and higher level Echo Return Loss Enhancement (ERLE) around the steady state.

This paper proposes an alternative learning algorithm for a stereophonic acoustic echo canceller without pre-processing which can identify the correct echo-paths. By dividing the filter coefficients into the former/latter parts and updating them alternatively, conditions both for unique solution and for perfect echo cancellation are satisfied. The learning for each part is switched from one part to the other when that part converges. Convergence analysis clarifies the condition for correct echo-path identification. For fast and stable convergence, a convergence detection and an adaptive step-size are introduced. The modification amount of the filter coefficients determines the convergence state and the step-size. Computer simulations show 10 dB smaller filter coefficient error than those of the conventional algorithms without pre-processing.

In order to perform the registration of virtual objects in vision-based augmented reality systems, the estimation of the relation between the real and virtual worlds is needed. This paper presents a three-point vision-based registration method for video see-through augmented reality systems using binocular cameras. The proposed registration method is based on a combination of monocular and stereoscopic registration methods. A correction method that performs an optimization of the registration by correcting the 2D positions in the images of the marker feature points is proposed. Also, an extraction strategy based on color information is put forward to allow the system to be robust to fast user's motion. In addition, a quantification method is used in order to evaluate the stability of the produced registration. Timing and stability results are presented. The proposed registration method is proven to be more stable than the standard stereoscopic registration method and to be independent of the distance. Even when the user moves quickly, our developed system succeeds in producing stable three-point based registration. Therefore, our proposed methods can be considered as interesting alternatives to produce the registration in binocular augmented reality systems when only three points are available.

This paper deals with a first evaluation of the efficiency and the robustness of the real-time "v-disparity" algorithm in stereovision for generic road obstacles detection towards various types of obstacles (vehicle, pedestrian, motorbike, cyclist, boxes) and under adverse conditions (day, night, rain, glowing effect, noise and false matches in the disparity map). The theoretical good properties of the "v-disparity" algorithm--accuracy, robustness, computational speed--are experimentally confirmed. The good results obtained allow us to use this stereo algorithm as the onboard perception process for Driving Safety Assistance: conductor warning and longitudinal control of a low speed automated vehicle (using a second order sliding mode control) in difficult and original situations, at frame rate using no special hardware. Results of experiments--Vehicle following at low speed, Stop'n'Go, Stop on Obstacle (pedestrian, fallen motorbike, load dropping obstacle)--are presented.

During the period from dusk to dark, when it is difficult for drivers to see other vehicles, or when visibility is poor due to rain, snow, etc., the contrast between nearby vehicles and the background is lower. Under such conditions, conventional surveillance systems have difficulty detecting the outline of nearby vehicles and may thus fail to recognize them. To solve this problem, we have developed a rear and side surveillance system for vehicles that uses image processing. The system uses two stereo cameras to monitor the areas to the rear and sides of a vehicle, i.e., a driver's blind spots, and to detect the positions and relative speeds of other vehicles. The proposed system can estimate the shape of a vehicle from a partial outline of it, thus identifying the vehicle by filling in the missing parts of the vehicle outline. Testing of the system under various environmental conditions showed that the rate of errors (false and missed detection) in detecting approaching vehicles was reduced to less than 10%, even under conditions that are problematic for conventional processing.

Finding corresponding edges is considered being the most difficult part of edge-based stereo matching algorithms. Usually, correspondence for a feature point in the first image is obtained by searching in a predefined region of the second image, based on epipolar line and maximum disparity. Reduction of search region can increase performances of the matching process, in the context of execution time and accuracy. Traditionally, hierarchical multiresolution techniques, as the fastest methods are used to decrease the search space and therefore increase the processing speed. Considering maximum of directional derivative of disparity in real scenes, we formulated some relations between maximum search space in the second images with respect to relative displacement of connected edges (as the feature points), in successive scan lines of the first images. Then we proposed a new matching strategy to reduce the search space for edge-based stereo matching algorithms. Afterward, we developed some fast stereo matching algorithms based on the proposed matching strategy and the hierarchical multiresolution techniques. The proposed algorithms have two stages: feature extraction and feature matching. We applied these new algorithms on some stereo images and compared their results with those of some hierarchical multiresolution ones. The execution times of our proposed methods are decreased between 30% to 55%, in the feature matching stage. Moreover, the execution time of the overall algorithms (including the feature extraction and the feature matching) is decreased between 15% to 40% in real scenes. Meanwhile in some cases, the accuracy is increased too. Theoretical investigation and experimental results show that our algorithms have a very good performance with real complex scenes, therefore these new algorithms are very suitable for fast edge-based stereo applications in real scenes like robotic applications.

This letter proposes a 3-D stereo endoscopic image processing system. Whereas a conventional 3-D stereo endoscopic system has simple monitoring functions, the proposed system gives doctors exact depth feelings by providing them depth value information, visualization, and stereo PACS viewer to aid an education, accurate diagnosis, a surgical operation, and to further apply in a robotic surgery.

We suggest the method to recover the 3D shape of an object by using a color image scanner which has three light sources. The photometric stereo is traditional to recover the surface normals of objects using multiple light sources. In this method, it usually assumes distant light sources to make the optical models simple. But the light sources in the image scanner are so close to an object that the illuminant intensity varies with the distance from the light source, therefore these light sources should be modeled as the linear light sources. In this method, by using these models and two step algorithm; the initial estimation by the iterating computation and the optimization by the non-linear least square method, not only the surface normal but also the absolute distance from the light source to the surface can be estimated. By using this method, we can recover the 3D shape more precisely. In the experimental results, the 3D shape of real objects can be recovered and the effectiveness of the proposed method is shown.

In a real-time vision system, parallel memory access is essential for highly parallel image processing. The use of multiple memory modules is one efficient technique for parallel access. In the technique, data stored in different memory modules can be accessed in parallel. This paper presents an optimal memory allocation methodology to map data to be read in parallel onto different memory modules. Based on the methodology, a high-performance VLSI processor for three-dimensional instrumentation is proposed.

In designing a field-programmable gate array (FPGA)-based processor for motion stereo, a parallel memory system and a simple interconnection network for parallel data transfer are essential for parallel image processing. This paper, firstly, presents an FPGA-oriented hierarchical memory system. To reduce the bandwidth requirement between an on-chip memory in an FPGA and external memories, we propose an efficient scheduling: Once pixels are transferred to the on-chip memory, operations associated with the data are consecutively performed. Secondly, a rectangular memory allocation is proposed which allocates pixels to be accessed in parallel onto different memory modules of the on-chip memory. Consequently, completely parallel access can be achieved. The memory allocation also minimizes the required capacity of the on-chip memory and thus is suitable for FPGA-based implementation. Finally, a functional unit allocation is proposed to minimize the complexity between memory modules and functional units. An experimental result shows that the performance of the processor becomes 96 times higher than that of a 400 MHz Pentium II.

By using full-color light emitting diode (LED) panel, we have been studying a stereoscopic full-color large television in broad daylight. In order to implement stereoscopic large display for the general public, optimum parameters of display elements and parallax barrier and viewing areas of stereoscopic display using parallax barrier are discussed. Although stereoscopic display with parallax barrier permits the viewer to view stereoscopic images without any special glasses, its viewing area is restricted by crosstalk and disappearing of pixels. Enlarged viewing areas, which are derived from the small ratio of light emitting region to pixel and a proper aperture ratio of parallax barrier, are analyzed. A model of a viewer standing toward the display is proposed because the viewer apart from the horizontal center of the display turns to the center point of LED display and this turning causes a deviation of viewer's eye position. Then, the allowable number of viewing locations is derived on "no crosstalk" and "no disappearance" conditions. The optimum aperture ratio of parallax barrier and the width of light emitting region is obtained through the optimization. The viewing area obtained from the analysis is confirmed by experiments using full-color LED panel. Relations between viewing area and the moire fringes is also discussed. The depth of the viewing area agrees the viewing distance where no moire fringe appears. Furthermore, possibility of display for the crowds is discussed.

This paper has two parts. In the first part of the paper, we note the property that under the para perspective camera projection model of a camera, the set of 2D images produced by a 3D point can be optimally represented by two lines in the affine space (α-β space). The slope of these two lines are same, and we observe that this constraint is exactly the same as the epipolar line constraint. Using this constraint, the equation of the epipolar line can be derived. In the second part of the paper, we use the "same slope" property of the lines in the α-β space to derive the affine structure of the human face. The input to the algorithm is not limited to an image sequence of a human head under rigid motion. It can be snapshots of the human face taken by the same or different cameras, over different periods of time. Since the depth variation of the human face is not very large, we use the para perspective camera projection model. Using this property, we reformulate the (human) face structure reconstruction problem in terms of the much familiar multiple baseline stereo matching problem. Apart from the face modeling aspect, we also show how we use the results for reprojecting human faces in identification tasks.

In this paper, we propose an elegant approach for illumination invariant face recognition based on the photometric stereo technique. The basic idea is to reconstruct the surface normal and the albedo of a face using photometric stereo images, and then use them as the illumination independent model of the face. And, we have investigated the optimal light source directions for accurate surface shape reconstruction, and the robust estimation technique for the illumination direction of an input face image. We have tested the proposed algorithm with 125 real face images of 25 persons which are taken under 5 quite different illumination conditions, and achieved the success rate of more than 80%. Comparison results of conventional face recognition methods and the proposed method are also evaluated. These results demonstrate that the proposed technique have a great potential for the robust face recognition even when the lighting condition changes severely.

This paper proposes a new method for reconstruction a shape of skin surface replica from shaded image sequence taken with different light source directions. Since the shaded images include shadows caused by surface height fluctuation, and specular and inter reflections, the conventional photometric stereo method is not suitable for reconstructing its surface accurately. In the proposed method, we choose measured intensity which does not include specular and inter reflections and self-shadows so that we can calculate accurate normal vector from the selected measured intensity using SVD (Singular Value Decomposition) method. The experimental results from real images demonstrate that the proposed method is effective for shape reconstruction from shaded images, which include specular and inter reflections and self-shadows.

A new method to recover and display 3D fundus pattern on the inner bottom surface of eye-ball from stereo fundus image pair is developed. For the fundus stereo images, a simple stereo technique does not work, because the fundus is observed through eye lens and a contact wide-angle enlarging lens. In this method, utilizing the fact that fundus forms a part of sphere, we identify their optical parameters and correct the skews of the lines-of-sight. Then, we obtain 3D images of the fundus by back-projecting the stereo images.