1. A method for determination of human behavior alerts from a video stream, the method comprising: parsing a video stream via a programmable device into a plurality of segments, each of the segments either temporally related to at least one of a plurality of temporally distinct transactions in an event data log, or associated with a pseudo transaction marker if not temporally related to at least one of the temporally distinct transactions and an image analysis of said not temporally related segment indicates a temporal correlation with at least one of the distinct transactions is expected, by: defining each segment as spanning three consecutive temporally distinct transactions, each within a specified time threshold of a next one of the temporally distinct transactions; identifying a one segment occurring between a first and a second of the consecutive temporally distinct transactions wherein a time gap between the first and the second transactions is longer than the specified threshold; performing an automated analysis of the one segment occurring between the first and the second transactions to determine a presence of an expected specified visual activity; and associating the one segment occurring between the first and the second transactions with the pseudo transaction if an expected specified visual activity is determined by the performed automated analysis; extracting visual image features from the segments; performing a one-support vector machine classification on the extracted segment features to categorize the segments into inliers or outliers relative to a threshold boundary; and issuing event of concern alerts with respect to each of the inlier segments associated with the associated pseudo transaction marker; and wherein the performing the automated analysis of the one segment occurring between the first and the second transactions to determine the presence of the expected specified visual activity comprises: taking locally maximum points of a squared weighted gradient norm function as interest points in the one segment; extracting averaged color values and image gradient vectors relevant to the interest points; and composing color feature vectors from the extracted averaged color values and the extracted image gradient vectors.