Abstract:
Apparatuses, methods and storage medium associated with processing an image are disclosed herein. In embodiments, a method for processing one or more images may include generating a plurality of pairs of keypoint features for a pair of images. Each pair of keypoint features may include a keypoint feature from each image. Further, for each pair of keypoint features, corresponding adjoin features may be generated. Additionally, for each pair of keypoint features, whether the adjoin features are similar may be determined. Whether the pair of images have at least one similar object may also be determined, based at least in part on a result of the determination of similarity between the corresponding adjoin features. Other embodiments may be described and claimed.
Abstract:
A motion manifold system analyzes a set of videos, identifying image patches within those videos corresponding to regions of interest and identifying patch trajectories by tracking the movement of the regions over time in the videos. Based on the patch identification and tracking, the system produces a motion manifold data structure that captures the way in which the same semantic region can have different visual representations over time. The motion manifold can then be applied to determine the semantic similarity between different patches, or between higher-level constructs such as images or video segments, including detecting semantic similarity between patches or other constructs that are visually dissimilar.
Abstract:
A method for comparing a first image with a second image is provided. The method comprises identifying first keypoints in the first image and second keypoints in the second image and associating each first keypoint with a corresponding second keypoint in order to form a corresponding keypoint match. For each pair of first keypoints, the method further comprises calculating the distance therebetween for obtaining a corresponding first length. Similarly, for each pair of second keypoints, the method comprises calculating the distance therebetween for obtaining a corresponding second length. The method further comprises calculating a plurality of distance ratios; each distance ratio is based on a length ratio between a selected one between a first length and a second length and a corresponding selected one between a second length and a first length, respectively. The method still further includes calculating a statistical distribution of the plurality of distance ratios and generating a model function expressing a statistical distribution of further distance ratios corresponding to a random selection of keypoints in the first and second images. The method includes comparing said statistical distribution of the plurality of distance ratios with said model function, and assessing whether the first image contains a view of an object depicted in the second image based on said comparison.
Abstract:
An information processing apparatus acquires a plurality of geometric features and normals at the respective geometric features from a target object arranged at the first position. The information processing apparatus also acquires a plurality of normals corresponding to the respective geometric features of the target object from a shape model for the target object that is arranged at the second position different from the first position. The information processing apparatus calculates direction differences between the acquired normals for respective pairs of corresponding geometric features of the target object and shape model. The information processing apparatus determines whether or not occlusion occurs at each geometric feature by comparing the calculated direction differences with each other.
Abstract:
A face illumination normalization method includes acquiring a digital image including a face that appears to be illuminated unevenly. One or more uneven illumination classifier programs are applied to the face data to determine the presence of the face within the digital image and/or the uneven illumination condition of the face. The uneven illumination condition may be corrected to thereby generate a corrected face image appearing to have more uniform illumination, for example, to enhance face recognition.
Abstract:
A pattern processing system associates image input patterns with desired response codes. The image input is stored in an image buffer as an addressable array of sample values. An address sequencer provides a sequence of addresses (or 'address stream') to the image buffer and to a response memory. The next address provided by the address sequencer is based upon the current address and the state of the sample value stored in the image buffer at the location corresponding to the current address. Once the address sequencer repeats an address, the address stream is in a repetitive address loop as long as the image stored in the image buffer remains constant. The addressing occurring commonly for the learning samples are detected and subsequently used for identification of unknown patterns. By arranging the sequence generator so as to ensure that the address-sequences have a predetermined minimum length, multiple possible address-sequences are avoided.
Abstract:
A universal symbolic handwriting recognition system (24) for converting user entered time ordered stroke sequences (18) into computer (26) readable text is described. The system (24) operates on two levels: (1) a word-level recognizer, which recognizes the entire group of strokes as a unit and (2) a parser-level recognizer, which breaks the strokes into segments and recognizes groups of stroke segments within a word, thus recognizing separate characters or character sequences within a word to build a complete recognition string. In both recognition levels, the system trains on actual user samples, either on an entire word, or on a character or character sequence within a word.