Building light-weight single shot refinement neural network for vehicle passenger detection system

Abstract

Methods and systems for vehicle passenger detection, can involve extracting a region of interest from one or more images of a vehicle captured by one or more cameras, image-processing of the region of interest and detecting faces in the region of interest with a pruned deep neural-network based object-detection module of a neural network comprising a pruned network, and utilizing the pruned network for inference to determine a number of passengers in the vehicle. The neural network can be pruned by identifying filter pairs in the neural network having a high correlation of weights to detect features have redundant features, and iteratively removing the filter pairs wherein the neural network is retrained after the iterative removal of the filter pairs.

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