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.

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.

Abstract: A method and system for image processing of an image captured by an image-capturing device, can involve dividing a region of interest in an image into blocks, wherein the image is captured by an image-capturing device. The region of interest can be associated with one or more faces in the image, and a resulting division of the dividing of the region of interest may be non-uniform. A minimum block size can be defined and the coordinates of each block after dividing of the region of interest in the image into the blocks. The one or more faces in the image can be redacted and reconstructed using the coordinates. In addition, redacting and reconstructing of the image is reversible for use with detecting the one or more faces in the image. The coordinates can specify top left coordinates and bottom right coordinates of each block.

Abstract: A method and system for image processing of an image captured by an image-capturing device, can involve dividing a region of interest in an image into blocks, wherein the image is captured by an image-capturing device. The region of interest can be associated with one or more faces in the image, and a resulting division of the dividing of the region of interest may be non-uniform. A minimum block size can be defined and the coordinates of each block after dividing of the region of interest in the image into the blocks. The one or more faces in the image can be redacted and reconstructed using the coordinates. In addition, redacting and reconstructing of the image is reversible for use with detecting the one or more faces in the image. The coordinates can specify top left coordinates and bottom right coordinates of each block.