Abstract:
Disclosed are a system, apparatus, and method for in-situ creation of planar natural feature targets. In one embodiment, a planar target is initialized from a single first reference image one or more subsequent images are processed. In one embodiment, the planar target is tracked in six degrees of freedom upon the processing of the one or more subsequent images and a second reference image is selected from the processed one or more subsequent images. In one embodiment, upon selecting the second reference image the planar target is refined to a more accurate planar target.
Abstract:
Disclosed are a system, apparatus, and method for in-situ creation of planar natural feature targets. In one embodiment, a planar target is initialized from a single first reference image one or more subsequent images are processed. In one embodiment, the planar target is tracked in six degrees of freedom upon the processing of the one or more subsequent images and a second reference image is selected from the processed one or more subsequent images. In one embodiment, upon selecting the second reference image the planar target is refined to a more accurate planar target.
Abstract:
Methods, systems, computer-readable media, and apparatuses for assigning a color class of a defined finite set of colors to at least one sub-region within a test image are presented. A plurality of sub-regions are identified within a test image. A first sub-region color value is determined for a selected first sub-region of the test image. Using the first sub-region color value and a plurality of zero-order probability distributions, a first color class of the defined finite set of colors is determined as a hypothesis color for the first sub-region. A second sub-region color value is determined for a selected second sub-region of the test image. Using the second sub-region color value and a conditional probability distribution conditioned on the hypothesis color for the first sub-region, a second color class of the defined set of colors is determined. The second color class is assigned to the second sub-region.
Abstract:
Disclosed is a server that can perform a visual search using at least one rectified image. A method implemented at a server includes storing a plurality of images with the server, receiving at least one rectified image having at least one potential object of interest from a computing device for a visual search, and extracting descriptors representing features of the at least one rectified image. The extracted descriptors of the at least one rectified image are designed to be invariant to rotation, scale, and lighting without needing to be invariant to perspective or affine distortion.
Abstract:
Various methods, apparatuses and/or articles of manufacture are provided which may be implemented for use by an electronic device to track objects across two or more digital images. For example, an electronic device may generate a plurality of warped patches corresponding to a reference patch of a reference image, and combine two or more warped patches to form a blurred warped patch corresponding to the reference patch with a motion blur effect applied to a digital representation corresponding to a keypoint of an object to be tracked.
Abstract:
Systems, apparatus and methods to create a database by a device (such as a server) and to use the database by a mobile device for detecting a planar target are presented. The database allows recognition of a planar target by a mobile device from steeper angles with minimum impact on runtime. The database is created from at least one warped view of the planar target. For example, a database may contain keypoints and descriptors from a non-warped view and also from one or more warped views. The database may be pruned by removing keypoints and corresponding descriptors of one image (e.g., a warped image) overlapping with similar or identical keypoints and descriptors of another image (e.g., a non-warped image).
Abstract:
A computer-implemented method of tracking a target object in an object recognition system includes acquiring a plurality of images with a camera and simultaneously tracking the target object and dynamically building online map data from the plurality of images. Tracking of the target object is based on the online map data and the offline map data. In one aspect, tracking the target object includes enabling only one of the online map data and offline map data for tracking based on whether tracking is successful. In another aspect, tracking the target object includes fusing the online map data with the offline map data to generate a fused online model.
Abstract:
A computer-implemented method of tracking a target object in an object recognition system includes acquiring a plurality of images with a camera. The method further includes simultaneously tracking the target object and dynamically building environment map data from the plurality of images. The tracking of the target object includes attempting to estimate a target pose of the target object with respect to the camera based on at least one of the plurality of images and based on target map data. Next, the method determines whether the tracking of the target object with respect to the camera is successful. If not, then the method includes inferring the target pose with respect to the camera based on the dynamically built environment map data. In one aspect the method includes fusing the inferred target pose with the actual target pose even if tracking is successful to improve robustness.
Abstract:
Methods, systems, computer-readable media, and apparatuses for assigning a color class of a defined finite set of colors to at least one sub-region within a test image are presented. A plurality of sub-regions are identified within a test image. A first sub-region color value is determined for a selected first sub-region of the test image. Using the first sub-region color value and a plurality of zero-order probability distributions, a first color class of the defined finite set of colors is determined as a hypothesis color for the first sub-region. A second sub-region color value is determined for a selected second sub-region of the test image. Using the second sub-region color value and a conditional probability distribution conditioned on the hypothesis color for the first sub-region, a second color class of the defined set of colors is determined. The second color class is assigned to the second sub-region.
Abstract:
Method, mobile device, computer program product and apparatus for performing a search are disclosed. The method of performing a search comprises receiving one or more images of an environment in view of a mobile device, generating a simultaneous localization and mapping of the environment using the one or more images, wherein the simultaneous localization and mapping of the environment comprises a plurality of map points representing a plurality of surfaces in a three dimensional coordinate system of the environment, sending a set of the plurality of map points as a search query to a server, receiving a query response from the server, and identifying an object in the environment based at least in part on the query response.