Abstract:
Systems and methods are provided for alternating projection of content and capturing an image. The method includes steps of projecting, by a projection device, content at a first rate, projecting, by the projection device, a capture frame at a second rate, and capturing, by an image capture device, an image including the capture frame at the second rate, wherein capturing the image comprises capturing the image when the capture frame is projected. Systems and methods provided herein may provide increased tracking accuracy by a projecting a capture frame that does not obscure features in the image.
Abstract:
A mobile device determines a vision based pose using images captured by a camera and determines a sensor based pose using data from inertial sensors, such as accelerometers and gyroscopes. The vision based pose and sensor based pose are used separately in a visualization application, which displays separate graphics for the different poses. For example, the visualization application may be used to calibrate the inertial sensors, where the visualization application displays a graphic based on the vision based pose and a graphic based on the sensor based pose and prompts a user to move the mobile device in a specific direction with the displayed graphics to accelerate convergence of the calibration of the inertial sensors. Alternatively, the visualization application may be a motion based game or a photography application that displays separate graphics using the vision based pose and the sensor based pose.
Abstract:
An apparatus and method for generating parameters for an application, such as an augmented reality application (AR app), using camera pose and gyroscope rotation is disclosed. The parameters are estimated based on pose from images and rotation from a gyroscope (e.g., using least-squares estimation with QR factorization or a Kalman filter). The parameters indicate rotation, scale and/or non-orthogonality parameters and optionally gyroscope bias errors. In addition, the scale and non-orthogonality parameters may be used for conditioning raw gyroscope measurements to compensate for scale and non-orthogonality.
Abstract:
A system for storing target images for object recognition predicts a querying performance for the target image if the target image were included in a search tree of a database. The search tree has a universal search tree structure that is fixed so that it does not change with the addition of new target images. The target image is selected for inclusion or exclusion in the search tree based on the querying performance, wherein the fixed tree structure of the search tree does not change if inclusion of the target image is selected.
Abstract:
A master device images an object device and uses the image to identify the object device. The master device then automatically interfaces with the identified object device, for example, by pairing with the object device. The master device may receive broadcast data from the object device including information about the visual appearance of the object device and use the broadcast data in the identification of the object device. The master device may retrieve data related to the object device and display the related data, which may be display the data over the displayed image of the object device. The master device may provide an interface to control the object device or be used to pass data to the object device.
Abstract:
An example system includes a first computing device comprising a first graphics processing unit (GPU) implemented in circuitry, and a second computing device comprising a second GPU implemented in circuitry. The first GPU is configured to determine graphics primitives of a computer graphics scene that are visible from a camera viewpoint, generate a primitive atlas that includes data representing the graphics primitives that are visible from the camera viewpoint, and shade the visible graphics primitives in the primitive atlas to produce a shaded primitive atlas. The second GPU is configured to render an image using the shaded primitive atlas.
Abstract:
An example system includes a first computing device comprising a first graphics processing unit (GPU) implemented in circuitry, and a second computing device comprising a second GPU implemented in circuitry. The first GPU is configured to perform a first portion of an image rendering process to generate intermediate graphics data and send the intermediate graphics data to the second computing device. The second GPU is configured to perform a second portion of the image rendering process to render an image from the intermediate graphics data. The first computing device may be a video game console, and the second computing device may be a virtual reality (VR) headset that warps the rendered image to produce a stereoscopic image pair.
Abstract:
A method for defining a sensor model includes determining a probability of obtaining a measurement from multiple potential causes in a field of view of a sensor modeled based on a stochastic map. The stochastic map includes a mean occupancy level for each voxel in the stochastic map and a variance of the mean occupancy level for each pixel. The method also includes determining a probability of obtaining an image based on the determined probability of obtaining the measurement. The method further includes planning an action for a robot, comprising the sensor, based on the probability of obtaining the image.
Abstract:
A method for generating a map includes determining an occupancy level of each of multiple voxels. The method also includes determining a probability distribution function (PDF) of the occupancy level of each voxel. The method further includes performing an incremental Bayesian update on the PDF to generate the map based on a measurement performed after determining the PDF.
Abstract:
Method, apparatus, and computer program product for merging multiple maps for computer vision based tracking comprises receiving a plurality of maps of a scene in a venue from at least one mobile device, identifying multiple keyframes of the plurality of maps of the scene, and eliminating redundant keyframes to generate a global map of the scene.