Abstract:
A three-dimensional pose of the head of a subject is determined based on depth data captured in multiple images. The multiple images of the head are captured, e.g., by an RGBD camera. A rotation matrix and translation vector of the pose of the head relative to a reference pose is determined using the depth data. For example, arbitrary feature points on the head may be extracted in each of the multiple images and provided along with corresponding depth data to an Extended Kalman filter with states including a rotation matrix and a translation vector associated with the reference pose for the head and a current orientation and a current position. The three-dimensional pose of the head with respect to the reference pose is then determined based on the rotation matrix and the translation vector.
Abstract:
A multi-user augmented reality (AR) system operates without a previously acquired common reference by generating a reference image on the fly. The reference image is produced by capturing at least two images of a planar object and using the images to determine a pose (position and orientation) of a first mobile platform with respect to the planar object. Based on the orientation of the mobile platform, an image of the planar object, which may be one of the initial images or a subsequently captured image, is warped to produce the reference image of a front view of the planar object. The reference image may be produced by the mobile platform or by, e.g., a server. Other mobile platforms may determine their pose with respect to the planar object using the reference image to perform a multi-user augmented reality application.
Abstract:
A database for object recognition is modified based on feedback information received from a mobile platform. The feedback information includes information with respect to an image of an object captured by the mobile platform. The feedback information, for example, may include the image, features extracted from the image, a confidence level for the features, posterior probabilities of the features belonging to an object in the database, GPS information, and heading orientation information. The feedback information may be used to improve the database pruning, add content to the database or update the database compression efficiency. The information feedback to the server by the mobile platform may be determined based on a search of a portion of the database performed by the mobile platform using features extracted from a captured query image.
Abstract:
Systems and methods are described herein for updating documents in a distributed network. When a new document needs to be added to the network, or when changes are to be made to an existing document, keywords are extracted from the document and used to generate update messages for each keyword. The nodes responsible for each keyword are determined. The individual update messages are consolidated into a composite update messages that is sent to a first node in the network. The first node extracts those portions of the composite message associated with it, and forwards the composite message to a second node in the network.
Abstract:
A database for object recognition is generated by performing at least one of intra-object pruning and inter-object pruning, as well as keypoint clustering and selection. Intra-object pruning removes similar and redundant keypoints within an object and different views of the same object, and may be used to generate and associate a significance value, such as a weight, with respect to remaining keypoint descriptors. Inter-object pruning retains the most informative set of descriptors across different objects, by characterizing the discriminability of the keypoint descriptors for all of the objects and removing keypoint descriptors with a discriminability that is less than a threshold. Additionally, a mobile platform may download a geographically relevant portion of the database and perform object recognition by extracting features from the query image and using determined confidence levels for each query feature during outlier removal.
Abstract:
Methods and apparatus are described herein for performing AND/OR searching using multiple keywords. A query is received at a first node in a network having multiple keywords. The first node determines a set of documents matching a first of the multiple keywords, and computes an ideal Bloom filter representing those keywords. The first node sends the query and the Bloom filter to a second node, which determines its search results for a second of the multiple keywords in accordance with the Bloom filter.
Abstract:
Systems and methods are described herein for updating documents in a distributed network. When a new document needs to be added to the network, or when changes are to be made to an existing document, keywords are extracted from the document and used to generate update messages for each keyword. The nodes responsible for each keyword are determined. The individual update messages are consolidated into a composite update messages that is sent to a first node in the network. The first node extracts those portions of the composite message associated with it, and forwards the composite message to a second node in the network.
Abstract:
Reference free tracking of position by a mobile platform is performed using images of a planar surface. Tracking is performed optical flow techniques, such as pyramidal Lucas-Kanade optical flow with multiple levels of resolution, where displacement is determined with pixel accuracy at lower resolutions and at sub-pixel accuracy at full resolution, which improves computation time for real time performance. Periodic drift correction is performed by matching features between a current frame and a keyframe. The keyframe may be replaced with the drift corrected current image.
Abstract:
In one example, an apparatus includes a processor configured to extract a first set of one or more keypoints from a first set of blurred images of a first octave of a received image, calculate a first set of one or more descriptors for the first set of keypoints, receive a confidence value for a result produced by querying a feature descriptor database with the first set of descriptors, wherein the result comprises information describing an identity of an object in the received image, and extract a second set of one or more keypoints from a second set of blurred images of a second octave of the received image when the confidence value does not exceed a confidence threshold. In this manner, the processor may perform incremental feature descriptor extraction, which may improve computational efficiency of object recognition in digital images.
Abstract:
Techniques are described for specifying a destination of a network policy, such as redirect or span policy, to be a logical set of ports (i.e., ports belonging to a port-profile or a port group) where the members of the set of ports may be added/removed dynamically without requiring any changes to the network policy. Further, a network administrator (or other user) may predefine the destinations for a network policy even before some or all of the destinations are active on a given virtualized system. In such cases, the network policies may go into effect when the required entities become available.