METHOD AND APPARATUS FOR INTEGRATION OF DETECTED OBJECT IDENTIFIERS AND SEMANTIC SCENE GRAPH NETWORKS FOR CAPTURED VISUAL SCENE BEHAVIOR ESTIMATION

摘要

A computer system executing code instructions of a visual scene feature extractor and classifier system comprising a processor executing object recognition on a captured image of a visual scene of interest including a plurality of objects in the visual scene of interest to identify a first object from the plurality of objects with a set of feature attributes wherein the feature attributes include an image view of the first object where the processor executing code instructions for the visual scene feature extractor and classifier to generate a first feature vector value for a first feature attribute of the first object. The processor to generate a first feature space including a neighborhood of labeled, previously-observed first feature vector values around the first feature vector value and to generate a second feature vector value for a second feature attribute of the first object, wherein the second feature vector value is within a second feature space including a neighborhood of labeled, previously-observed second feature vector values and the processor to generate association edges between the first and second feature vector values and the first object and between labeled, previously-observed first and second feature vector values and candidate objects corresponding to previous observations to establish a multiple feature graph for the first object for determining weighted likelihood that the first object may be identified as at least one previously observed candidate object.