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• W2404949813 abstract "This paper proposed an energy efficient multi-view visual processing scheme for the visual sensor networks. The aim of this scheme is to reduce the energy consumption by reducing the amount of data that needs to be transmitted in the network. Two approaches are introduced to achieve this purpose. First, an image compression method based on the Set Partitioning in Hierarchical Trees [1] algorithm is implemented to reduce the size of images before transmitting them over the network. Second, in cases where the Field-of-View of different visual nodes is overlapped, the overlapping regions (redundant information) between the images will be identified at the host workstation to prevent them from being transmitted multiple times. This is to further reduce the data transmission. In this case, only one visual node is required to transmit the overlapping regions. The information obtained from the aforementioned visual node will be used to reconstruct the overlapping regions of other visual nodes at the host workstation. In other words, other visual nodes are only required to transmit the nonoverlapping regions. Instead of transmitting the entire image over the network, only part of it will be transmitted. The simulations results indicate that the proposed scheme can reduce the data transmission up to 50%. In addition, strip-based processing is adopted to reduce the memory consumption of the visual node. In this case, the images will be transferred and encoded in a strip-by-strip manner. This can help to lessen the on-chip memory requirement since it is not necessary to process the entire image at the same time." @default.
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• W2404949813 date "2012-01-01" @default.
• W2404949813 modified "2023-09-23" @default.
• W2404949813 title "Strip-based Multi-view Image Compression for Visual Sensor Networks." @default.
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