Compressed video recognition

A device, comprising:

• interface circuitry;
• and
• processing circuitry to:
• receive, via the interface circuitry, compressed video data, wherein the compressed video data comprises motion vectors and prediction residuals, wherein video data is encoded in the compressed video data using the motion vectors and the prediction residuals;
• extract a plurality of features from the compressed video data, wherein at least some of the features are based on the motion vectors and at least some of the features are based on the prediction residuals;
• and
• recognize content in the video data using an artificial neural network, wherein the artificial neural network is trained to recognize the content based on the plurality of features, wherein the artificial neural network comprises a plurality of convolutional neural networks (CNNs), wherein one or more of the CNN are trained to recognize the content in the video data based on at least a subset of the features, and wherein one or more of the CNNs are trained to recognize the content in the video data based on pixel values in the video data,
• wherein the plurality of CNNs are configured as a cascaded neural network having multiple decision stages,
• wherein a first decision stage uses motion vectors to attempt an early decision,
• wherein a subsequent decision stage uses prediction residuals if the first decision stage is unsuccessful, and
• wherein a final decision stage uses decompressed video data if the subsequent decision stage is unsuccessful.