1. A method for prioritizing the adjudication of object alerts as a function of relative visual attribute values, the method comprising: in response to detecting an object that is discernible and static within an image scene of a video data input, a processing unit: generating an alert; tracking the detected object over a tracking period of time; extracting low-level image features from the video data input that are relevant to the object over the tracking time period; learning and ranking relative strengths of each of a plurality of attributes from the extracted features, wherein the plurality of attributes comprises an abandonment attribute that indicates a level of likelihood of abandonment of the object, a foregroundness attribute that quantifies a level of separation of foreground image data of the object from a background model of the image scene, and a staticness attribute that quantifies a level of stability of dimensions of a bounding box of the object over time; and prioritizing the alert relative to other alerts according to a learned importance or relevance value generated from the relative abandonment, foregroundness and staticness attribute strengths.