A two-part predictive coder for multitask signal compression

Traditional compression techniques optimize signal fidelity under a bit rate constraint. However, signals are often not only reconstructed for human evaluation purposes but also analyzed by machines. This paper introduces a two-part predictive (2PP) coding architecture intended for signal compression with the dual purposes of preserving signal fidelity and feature fidelity. First we introduce the architecture of the 2PP coder, then we apply and evaluate it on two problems: scene classification and pedestrian detection. Tradeoffs between compression rate, mean-squared reconstruction error, and classification accuracy, are explored.