Abstract:
To improve precision of visual search processing, SIFT points within a query image are forward matched to features in each of a plurality of repository images and SIFT points within each repository image are backward matched to features within the query image. Forward-only, backward-only and forward-and-backward matches may be weighted differently in determining an image match. Two way matching may be triggered by query image bit rate in excess of a threshold or by a sum of weighted distances between matching points exceeding a threshold. Significant performance gains in eliminating false positive matches are achieved.
Abstract:
Global descriptors for images within an image repository accessible to a visual search server are compared based on order statistics processing including sorting (which is a non-linear transform) and heat kernel matching. Affinity scores are computed for Hamming distances between Fisher vector components corresponding to different clusters of global descriptors from a pair of images and normalized to [0, 1], with zero affinity scores assigned to non-active cluster pairs. Linear Discriminant Analysis is employed to determine a sorted vector of affinity scores to obtain a new global descriptor. The resulting global descriptors produce significantly more accurate matching.
Abstract:
An electronic device is provided. The electronic device includes processing circuitry. The processing circuitry is configured to receive a first image comprising an image of a first object and a second image comprising an image of a second object. The processing circuitry is also configured to identify a depth of the second object in the second image. The processing circuitry is further configured to insert the image of the first object into the second image at a depth position based on the depth of the second object. The processing circuitry is configured to generate to display the image of the first object and the image of the second object in the second image.
Abstract:
An electronic device is provided. The electronic device includes processing circuitry. The processing circuitry is configured to receive a first image comprising an image of a first object and a second image comprising an image of a second object. The processing circuitry is also configured to identify a depth of the second object in the second image. The processing circuitry is further configured to insert the image of the first object into the second image at a depth position based on the depth of the second object. The processing circuitry is configured to generate to display the image of the first object and the image of the second object in the second image.
Abstract:
To improve feature selection accuracy during a visual search, interest points within a query image are two-way matched to features in an affine transformed image or otherwise transformed version of the query image. A user device implements a method for selecting local descriptors in the visual search. The method includes: detecting a first set of interest points for the original image; computing an affine transform matrix; computing a new image as a transformation of the original image using the affine transform matrix; detecting a second set of interest points from the and new image; performing a two-way matching between the first set of interest points and the second set of interest points; sorting matching pairs according to a specified self-matching score (SMS); assigning an infinite value to SMS of unmatched interest points from the original image; selecting the interest points based on SMS. Significant performance gains reduce false positive matches.
Abstract:
To reduce communication costs and computational complexity, only a subset of ranked SIFT points within a query image for a visual search request is transmitted to the visual search server in each iteration of an incremental search. For each candidate match, a flag identifying the matching points is returned by the server for use in computing holistic (e.g., histogram) information for a bounding box within the query image including the matching points. Distance from that query image holistic information is used to reject images from a short list used for a subsequent iteration, if any. If all images are rejected or a match criteria is met during one iteration, the search may terminate early without consideration of remaining SIFT points.
Abstract:
A method comprises computing a color factor value indicating an amount of color gradients in at least one color channel from the query image. The method comprises combining the color-keypoints with the gray-keypoints when the color factor value is greater than a threshold. A method for performing a visual search comprises extracting a plurality of local descriptors from a query image and then selecting a subset of them based on various criteria's such as visual meaning score. A method comprises aggregating each mean vector for each visual codeword from distances between each visual codeword and local descriptors. The method comprises aggregating variance vector for each visual codeword from the distance between each visual codeword, and local descriptors. The method comprises transmitting aggregated mean vector information and aggregated variance vector information to a search server for efficient image retrieval.
Abstract:
A method comprises computing a color factor value indicating an amount of color gradients in at least one color channel from the query image. The method comprises combining the color-keypoints with the gray-keypoints when the color factor value is greater than a threshold. A method for performing a visual search comprises extracting a plurality of local descriptors from a query image and then selecting a subset of them based on various criteria's such as visual meaning score. A method comprises aggregating each mean vector for each visual codeword from distances between each visual codeword and local descriptors. The method comprises aggregating variance vector for each visual codeword from the distance between each visual codeword, and local descriptors. The method comprises transmitting aggregated mean vector information and aggregated variance vector information to a search server for efficient image retrieval.
Abstract:
A virtual reality (VR) headset configured to be worn by a user. The VR headset comprises: i) a forward-looking vision sensor for detecting objects in the forward field of view of the VR headset; ii) a downward-looking vision sensor for detecting objects in the downward field of view of the VR headset; iii) a controller coupled to the forward-looking vision sensor and the downward-looking vision sensor. The controller is configured to: a) detect a hand in a first image captured by the forward-looking vision sensor; b) detect an arm of the user in a second image captured by the downward-looking vision sensor; and c) determine whether the detected hand in the first image is a hand of the user.
Abstract:
A method and apparatus include extracting a global descriptor from a query image with a plurality of segments. The method also includes identifying segments with a desirable discriminating potential by analyzing data of the plurality of segments based on an available image database. The method also includes creating a bitmask where the identified segments are active. The method also includes masking any segment of the plurality of segments of the global descriptor that are inactive according to the bitmaskA method includes extracting a global descriptor from a query image and identifying one or more reference global descriptors. The method also includes determining a distance between the global descriptor and each of the one or more reference global descriptors. In addition, the method includes, responsive to the distance satisfying a threshold, adding an image associated with each of the one or more reference global descriptors that satisfy the threshold to a list.