Reducing computational overhead via predictions of subjective quality of automated image sequence processing

A method, comprising:

• applying an image sequence processing algorithm to each of a plurality of arbitrary temporal sequences of image frames to automatically generate an output video from each corresponding temporal sequence;
• automatically extracting a plurality of features from each temporal sequence;
• receiving a human subjective quality rating for each of the output videos;
• receiving a machine-learned predictive model generated from a combination of the features extracted from each temporal sequence and the human subjective quality ratings of the corresponding output videos;
• receiving a candidate set comprising a temporal sequence of image frames of an arbitrary scene captured via an imaging device;
• applying the predictive model to the candidate set to predict a quality score;
• the quality score defining a subjective quality of a corresponding output video that can be generated by the image sequence processing algorithm from the candidate set;
• and
• if the quality score exceeds a predetermined threshold, automatically applying the image sequence processing algorithm to generate the corresponding output video from the candidate set.

A computer-readable storage device having computer-executable instructions stored thereupon which, when executed by a computer, cause the computer to:

• receive a predictive model, the predictive model automatically generated from a combination of features extracted from a plurality of arbitrary temporal sequence of image frames and human subjective quality ratings of one or more output videos generated from the temporal sequences by an image sequence processing algorithm;
• receive a candidate set comprising a temporal sequence of image frames of an arbitrary scene;
• apply the predictive model to the candidate set to generate a quality score;
• the quality score defining a predicted subjective quality of a corresponding output video that can be generated by the image sequence processing algorithm from the candidate set;
• and
• if the predicted quality score exceeds a predetermined threshold, automatically apply the image sequence processing algorithm to generate and output the corresponding output video from the candidate set.