Target re-identification

Abstract

A computer implemented method and system for training a machine to identify a target within video data, the method comprising the steps of providing a training data set including identified labelled targets within video data having the same target within different video views. Generating, using a learning model, a bounding box action policy for determining required adjustments to a bounding box around a target in the video data by: generating a bounding box around a labelled target within a first view of the video data. Converting the target bounded by the bounding box to a quantitative representation. Determining a matching level between the quantitative representation and a quantitative representation of a further labelled target within the video data from a second view different to the first view. Looping the following steps one or more times, the looped steps comprising: using the bounding box action policy to determine an action to change the bounding box. Applying the determined action to change the bounding box to a new bounding box. Converting the target bounded by the new bounding box to a new quantitative representation. Determining a further matching level between the new quantitative representation and the quantitative representation of the labelled target within the video data from the second view. Applying a reward to the learning model to adjust the bounding box action policy based on an improvement in the matching level.

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