Discreet markers for user localization

This paper describes a localization method for wearable computer users. To realize applications of wearable computers like a navigation system, the position of a user is required for location-based services. Many localization methods in indoor environments have been proposed. One of the methods estimates user’s position using IR beacons or visual markers. However, these methods have problems of power supply and/or undesirable visual effects. In order to avoid the problems, we propose a new localization method which is based on using an IR camera and discreet markers consisting of translucent retro-reflectors. In the proposed method, to extract the regions of the markers from the captured images stably, the camera captures the reflection of IR LEDs which are flashed on and off synchronously. 1

Ultra-Shallow DoF Imaging Using Faced Paraboloidal Mirrors

Computer Vision - ACCV 2016: 13th Asian Conference on Computer Vision, Nov 20-24, 2016, Taipei, TaiwanWe propose a new imaging method that achieves an ultra-shallow depth of field (DoF) to clearly visualize a particular depth in a 3-D scene. The key optical device consists of a pair of faced paraboloidal mirrors with holes around their vertexes. In the device, a lens-less image sensor is set at one side of their holes and an object is set at the opposite side. The characteristic of the device is that the shape of the point spread function varies depending on both the positions of the target 3-D point and the image sensor. By leveraging this characteristic, we reconstruct a clear image for a particular depth by solving a linear system involving position-dependent point spread functions. In experiments, we demonstrate the effectiveness of the proposed method using both simulation and an actually developed prototype imaging system

Novel view synthesis with light-weight view-dependent texture mapping for a stereoscopic HMD

ICME 2017: 18th IEEE International Conference on Multimedia and Expo, July 10-14, 2017, Hong Kong, ChinaThe proliferation of off-the-shelf head-mounted displays (HMDs) let end-users enjoy virtual reality applications, some of which render a real-world scene using a novel view synthesis (NVS) technique. View-dependent texture mapping (VDTM) has been studied for NVS due to its photo-realistic quality. The VDTM technique renders a novel view by adaptively selecting textures from the most appropriate images. However, this process is computationally expensive because VDTM scans every captured image. For stereoscopic HMDs, the situation is much worse because we need to render novel views once for each eye, almost doubling the cost. This paper proposes light-weight VDTM tailored for an HMD. In order to reduce the computational cost in VDTM, our method leverages the overlapping fields of view between a stereoscopic pair of HMD images and pruning the images to be scanned. We show that the proposed method drastically accelerates the VDTM process without spoiling the image quality through a user study

ReMagicMirror: Action Learning Using Human Reenactment with the Mirror Metaphor

MMM 2017: 23rd International Conference on Multimedia Modeling, Jan 4-6, 2017, Reykjavik, Iceland,We propose ReMagicMirror, a system to help people learn actions (e.g., martial arts, dances). We first capture the motions of a teacher performing the action to learn, using two RGB-D cameras. Next, we fit a parametric human body model to the depth data and texture it using the color data, reconstructing the teacher’s motion and appearance. The learner is then shown the ReMagicMirror system, which acts as a mirror. We overlay the teacher’s reconstructed body on top of this mirror in an augmented reality fashion. The learner is able to intuitively manipulate the reconstruction’s viewpoint by simply rotating her body, allowing for easy comparisons between the learner and the teacher. We perform a user study to evaluate our system’s ease of use, effectiveness, quality, and appeal

Moving object detection from a point cloud using photometric and depth consistencies

ICPR 2016: 23rd International Conference on Pattern Recognition, Dec 4-8, 2016, Cancun, Mexico3D models of outdoor environments have been used for several applications such as a virtual earth system and a vision-based vehicle safety system. 3D data for constructing such 3D models are often measured by an on-vehicle system equipped with laser rangefinders, cameras, and GPS/IMU. However, 3D data of moving objects on streets lead to inaccurate 3D models when modeling outdoor environments. To solve this problem, this paper proposes a moving object detection method for point clouds by minimizing an energy function based on photometric and depth consistencies assuming that input data consist of synchronized point clouds, images, and camera poses from a single sequence captured with a moving on-vehicle system

Dense matching of two views with large displacement

This paper describes a method of establishing dense matching of two views with large displacements. The problem addressed is formulated as the minimization of an energy functional that combines a similarity term and a smoothness term. The minimization of the energy functional reduces to solving a large system of nonlinear equations which is a discretized version of the Euler-Lagrange equation for the energy minimization problem at each image point. A dense displacement map is computed by solving the system of equations using a coarse-to-fine approach. The method has been successfully experimented with two applications:(1) computing binocular disparities from stereo pair images and (2) computing a dense displacement vector field (optical flow) from two views in a time-varying image sequence.http://library.naist.jp/mylimedio/dllimedio/show.cgi?bookid=100009582&oldid=1688

Surface reconstruction from stereo images preserving discontinuities

This paper describes a method of surface reconstruction from binocular stereo images. The problem addressed is formulated as the minimization of an energy functional that integrates a similarity term and a smoothness term realizing a controlled-continuity constraint. The minimization reduces to solving a large system of non-linear equations which is a discretized version of Euler-Lagrange equation. A disparity map, which is a real-valued function of the image coordinates, is obtained by solving the system of equations through scale hierarchy. Initially assuming a flat (constant disparity) surface, the proposed method first finds a local minimum of energy functional at a coarse scale and then proceeds to finer scales by using the previous result as an initial estimate at the current scale. At the finest scale, discontinuities and occluded areas are detected from a computed disparity surface. The proposed method can compute a dense disparity map directly from stereo images preserving discontinuities.http://library.naist.jp/mylimedio/dllimedio/show.cgi?bookid=100009576&oldid=1687