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:
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.
Abstract:
Disclosed are a system, apparatus, and method for detecting objects. Input image frames may be received and distinct regions created within each frame. Descriptors may be extracted from the regions according to their associated probability. Extracted descriptors may be matched to reference descriptors. Votes or confidence is cast for particular regions according to region properties. The region properties may be determined from center voting methods based on vector intersection to other vectors or intersections with a region. The probability of selecting particular regions can increase with each vote or increase in confidence for a region. In response to updating probabilities, additional regions may be selected and additional descriptors may be extracted. Additional voting iterations can update the probability of selecting a next region. An object pose may be estimated in response to meeting one or more thresholds.
Abstract:
Techniques are presented for expanding a digital representation of a physical plane from a physical scene. In some aspects, a method may include determining an orientation and an initial portion of a physical plane in the scene, and subdividing a rectified image for the scene into a plurality of grid cells. For the grid cells, an image signature may be generated. A grid cell contiguous to the obtained initial portion of the plane is determined to include part of the plane. An iterative process may be performed for each neighboring grid cell from the grid cell contiguous to at least part of the obtained initial portion, determining whether the neighboring grid cell is to be included as part of the plane if the image signature of said neighboring grid cell is similar to the image signature of a grid cell already determined to be included as part of the plane.
Abstract:
Exemplary methods, apparatuses, and systems for performing object detection on a mobile device are disclosed. A reference dataset comprising a set of reference keyframes for an object captured in a plurality of different lighting environments is obtained. An image of the object in a current lighting environment is captured. Reference keyframes are grouped into respective subsets according to one or more of: a reference keyframe camera position and orientation (pose), a reference keyframe lighting environment, or a combination thereof. Feature points of the image are compared with feature points of the reference keyframes in each of the respective subsets. A candidate subset of reference keyframes from the respective subsets is selected in response to the comparing feature points. A reference keyframe from the candidate subset of reference keyframes is selected for triangulation with the image of the object.
Abstract:
Techniques are presented for expanding a digital representation of a physical plane from a physical scene. In some aspects, a method may include determining an orientation and an initial portion of a physical plane in the scene, and subdividing a rectified image for the scene into a plurality of grid cells. For the grid cells, an image signature may be generated. A grid cell contiguous to the obtained initial portion of the plane is determined to include part of the plane. An iterative process may be performed for each neighboring grid cell from the grid cell contiguous to at least part of the obtained initial portion, determining whether the neighboring grid cell is to be included as part of the plane if the image signature of said neighboring grid cell is similar to the image signature of a grid cell already determined to be included as part of the plane.
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:
Systems, methods, and devices are described for constructing a digital representation of a physical scene by obtaining information about the physical scene. Based on the information, an initial portion of a planar surface within the physical scene may be identified. In one aspect of the disclosure, constructing a digital representation of a physical scene may include obtaining information about the physical scene, identifying a planar surface within the physical scene, selecting a physical object within the physical scene, placed above the planar surface, detecting properties associated with the physical object, generating a three-dimensional (3D) reconstructed object using the properties associated with the physical object, and representing the planar surface as an augmented reality (AR) plane in an augmented reality environment, wherein the AR plane in the AR environment is capable of supporting 3D reconstructed objects on top of it.
Abstract:
Disclosed are a system, apparatus, and method for detecting objects. Input image frames may be received and distinct regions created within each frame. Descriptors may be extracted from the regions according to their associated probability. Extracted descriptors may be matched to reference descriptors. Votes or confidence is cast for particular regions according to region properties. The region properties may be determined from center voting methods based on vector intersection to other vectors or intersections with a region. The probability of selecting particular regions can increase with each vote or increase in confidence for a region. In response to updating probabilities, additional regions may be selected and additional descriptors may be extracted. Additional voting iterations can update the probability of selecting a next region. An object pose may be estimated in response to meeting one or more thresholds.