KEYWORDS: Deep learning, Video, RGB color model, Visualization, Systems modeling, Cameras, Video processing, Statistical modeling, Sensors, Pose estimation
First time spectators of fencing competitions cannot understand the complicated rules, making it difficult for them to enjoy the game. Therefore, in this paper, we propose a system that detects the situation of a fencing match using skeleton points extracted from videos. Players cannot be equipped with sensors or other devices to prevent interference with the match. Consequently, this research proposes a system that detects "phrases" using skeleton point information extracted from videos and displays the game situation. We evaluate actual videos of fencing to confirm the performance.
This paper presents very compact range image sensors for short distance measurement, which is suitable for robot hands, etc. Robot manipulation such as grasping is one of the applications that require a range image sensor to obtain threedimensional (3D) information of the target object. For such applications, it is necessary to avoid the occlusion by a robot manipulator or a robot hand while measurement, and it is effective to attach a sensor to the robot hand for the avoidance. For this aim, a range sensor that is small enough and can measure at the short distance is required. Two sensors are constructed in this paper: one uses a multi-slit laser projector and the other uses a multi-spot laser projector. A small laser projector and a small camera is combined and range images are obtained in real time using the principle of active stereo. Appropriate methods to obtain range image are proposed for both sensors, and especially for the one with a multislit laser projector, a method to use both disparity and the intensity of laser light image is presented. The effectiveness of the proposed sensors is verified through short-range object measurement experiments.
In this paper, a novel system that operates home appliances at arbitrary positions in a room is proposed based on a “command space” associated with the operation of the home appliance. In the proposed system, a hand waving gesture is used to operate the home appliances. First, three-dimensional (3D) positions are extracted from the hand waving gestures at two different positions, and a command space is set up based on the extracted 3D positions. Thus, it is possible to operate the home appliances freely in an arbitrary place chosen by the user by installing the user-definable command space. Next, detailed operations are performed by hand waving in the command space. Experiments were conducted to confirm that detailed operations, such as TV channel switching, can be executed from different places using the proposed system.
This paper proposes a novel approach that performs extrinsic parameter estimation of a camera installed in a man-made environment using a single image. The problem of extrinsic parameter calibration is identical to 6DoF (six-degrees of freedom) localization problem of the camera. We take advantage of line information that is usually present in the man-made environment such as inside of the building. Our approach only requires a flat surface map for a 3D environment model which can be easily obtained from the blueprint of the artificial environment (e.g., CAD data). In order to manage the complicated 6DoF search problem, we propose a novel image descriptor defined in quantized Hough space to perform 3D-2D matching process between line features from the 3D flat surface model and the 2D single image. The proposed method can robustly estimate the complete extrinsic parameters of the camera, as we demonstrate experimentally.
This paper introduces a simultaneous estimation method of the extrinsic parameters of multiple fish-eye cameras using simple calibration markers. Precise extrinsic parameters of cameras mounted on a car are important, for example, to provide a seamless overhead view image to the driver. Calibration markers are set in the area that are observable from adjacent two cameras. Extrinsic parameters of each camera are estimated individually and then combined and refined using a geometric constraint. Cube markers are chosen as the calibration markers. The method is evaluated by simulation and experiments using a real car. It is shown that extrinsic parameters are obtained by the proposed method and suggested that the errors of intrinsic parameters affect the estimation of extrinsic parameters.
This study aims at developing a practical stereo camera that is suitable for applications such as surveillance, in
which detection of anomalies or measurement of moving people are required. In such surveillance cases, targets
to measure usually move. In this paper, "Subtraction stereo" is proposed that focuses on motion information
to increase the robustness of the stereo matching. It realizes robust measurement of range images by detecting
moving regions with each camera and then applying stereo matching for the detected moving regions. Measurement
of three-dimensional position, height and width of a target object using the subtraction stereo is discussed.
The basic algorithm is implemented on a commercially available stereo camera, and the effectiveness of the
subtraction stereo is verified by several experiments using the stereo camera.
Various methods have been proposed until now for range measurement or three dimensional shape reconstruction. However, most of them need a large-scale equipment or a special environment. This paper proposes a technique which obtains a range image easily under a general environment using only an off-the-shelf digital camera. Distance is calculated by obtaining the irradiance of scene lighted by the flash of a digital camera using the fact that the intensity of reflected light of the flash is inversely proportional to the square of the distance from the object. The irradiance is obtained by subtracting an image without the flash from an image with the flash. The image without the flash is used to obtain the reflectance ratio at each pixel. The intensity of reflected light of the flash is affected by the inclination of the object surface. A method to estimate the inclination at each pixel is proposed which uses the change of the irradiance in adjacent pixels. The inclination is formulated as the function of the rate of change, and thus the inclination can be calculated by the rate which is easily obtained from the image. Additionally, color information is simultaneously obtained because visible light is used. Assumptions in the method are that the object surface has no specular reflection and the flash is set at the same position as the center of the lens. Experiments show that a range image is roughly obtained by the proposed method, and furthermore, that proper distance is obtained for inclined surfaces.
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