Visual object and event detection and prediction system using saccades

    公开(公告)号:GB2547752A

    公开(公告)日:2017-08-30

    申请号:GB201621726

    申请日:2016-12-20

    Applicant: IBM

    Abstract: A received image (1301) is divided into patches, which may have different sizes. A cluster-direction sequence (see fig. 6) is generated (1302) for each of a plurality of saccadic paths along the patches, the paths being given by a policy matrix (see figs. 8 & 9). The sequences are used to identify an object in the image. Path sequence generation using the matrix may comprise assigning (1303) a likelihood (which may be weighted (1304) using a total frequency of occurrence of the sequence in the matrix for a given class) that the image belongs to each class defined in the matrix, and identifying (1305) the object using a likelihood average over the sequences. Image context, e.g. previous observations or goal, may be used. The patches may be clustered into groups, e.g. using k-means clustering algorithm (see figs. 4&5). Specific salient features in an image may thus be identified, leading to a classification of the image by judging whether the salient features can identify a unique class of object (e.g. 9 MNIST digits, or image classes in ImageNet, e.g. cats, planes etc.) in the image with high probability. Classification may occur through progressive exclusion of other classes.

    Visual Object and Event Detection and Prediction System using Saccades

    公开(公告)号:GB2547752B

    公开(公告)日:2018-01-24

    申请号:GB201621726

    申请日:2016-12-20

    Applicant: IBM

    Abstract: A method of operating an image detection device includes receiving an image, dividing the image into a plurality of patches, grouping ones of the plurality of patches, generating a set of saccadic paths through the plurality of patches of the image, generating a cluster-direction sequence for each saccadic path, generating a policy function for identifying an object in a new image using a combination of the cluster-direction sequences, and operating the image detection device using the policy function to identify an object in the new image.

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