BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING

Min Jing; SA Coleman; Scotney Bryan; TM McGinnity

BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING

Min Jing, SA Coleman, Scotney Bryan, TM McGinnity

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

18 Downloads (Pure)

Abstract

Fast image processing is a key element in achieving real-time image and video analysis. The spiral addressing scheme has been an efficient tool for hexagonal image processing (HIP), whereby the image pixel indices are stored in a one-dimensional vector that enables fast processing. Unlike HIP, which requires a complex resampling scheme, we present a novel “squiral” (square spiral) image processing (SIP) framework that provides a spiral addressing scheme for direct application to standard square pixel-based images. A SIP-based non-overlapping convolution technique is developed by simulating the eye tremor phenomenon of the human visual system to accelerate computation in feature extraction. Furthermore, we deploy the proposed simulated eye tremor technique on a sequence of video frames. The preliminary results based on two action video clips demonstrate the potential of the SIP-based eye tremor model to facilitate fast video processing.

Original language	English
Title of host publication	Unknown Host Publication
Publisher	IEEE
Number of pages	5
Publication status	Published - 27 Sep 2015
Event	The International Conference on Image Processing (ICIP) - Quebec City, Canada Duration: 27 Sep 2015 → …

Conference

Conference	The International Conference on Image Processing (ICIP)
Period	27/09/15 → …

Keywords

spiral image processing
spiral addressing
eye tremor
non-overlapping convolution
video processing

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Cite this

@inproceedings{9e5e17186a9b47efa49874c74b5c428f,

title = "BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING",

abstract = "Fast image processing is a key element in achieving real-time image and video analysis. The spiral addressing scheme has been an efficient tool for hexagonal image processing (HIP), whereby the image pixel indices are stored in a one-dimensional vector that enables fast processing. Unlike HIP, which requires a complex resampling scheme, we present a novel “squiral” (square spiral) image processing (SIP) framework that provides a spiral addressing scheme for direct application to standard square pixel-based images. A SIP-based non-overlapping convolution technique is developed by simulating the eye tremor phenomenon of the human visual system to accelerate computation in feature extraction. Furthermore, we deploy the proposed simulated eye tremor technique on a sequence of video frames. The preliminary results based on two action video clips demonstrate the potential of the SIP-based eye tremor model to facilitate fast video processing.",

keywords = "spiral image processing, spiral addressing, eye tremor, non-overlapping convolution, video processing",

author = "Min Jing and SA Coleman and Scotney Bryan and TM McGinnity",

year = "2015",

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language = "English",

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AU - Jing, Min

AU - Coleman, SA

AU - Bryan, Scotney

AU - McGinnity, TM

PY - 2015/9/27

Y1 - 2015/9/27

N2 - Fast image processing is a key element in achieving real-time image and video analysis. The spiral addressing scheme has been an efficient tool for hexagonal image processing (HIP), whereby the image pixel indices are stored in a one-dimensional vector that enables fast processing. Unlike HIP, which requires a complex resampling scheme, we present a novel “squiral” (square spiral) image processing (SIP) framework that provides a spiral addressing scheme for direct application to standard square pixel-based images. A SIP-based non-overlapping convolution technique is developed by simulating the eye tremor phenomenon of the human visual system to accelerate computation in feature extraction. Furthermore, we deploy the proposed simulated eye tremor technique on a sequence of video frames. The preliminary results based on two action video clips demonstrate the potential of the SIP-based eye tremor model to facilitate fast video processing.

AB - Fast image processing is a key element in achieving real-time image and video analysis. The spiral addressing scheme has been an efficient tool for hexagonal image processing (HIP), whereby the image pixel indices are stored in a one-dimensional vector that enables fast processing. Unlike HIP, which requires a complex resampling scheme, we present a novel “squiral” (square spiral) image processing (SIP) framework that provides a spiral addressing scheme for direct application to standard square pixel-based images. A SIP-based non-overlapping convolution technique is developed by simulating the eye tremor phenomenon of the human visual system to accelerate computation in feature extraction. Furthermore, we deploy the proposed simulated eye tremor technique on a sequence of video frames. The preliminary results based on two action video clips demonstrate the potential of the SIP-based eye tremor model to facilitate fast video processing.

KW - spiral image processing

KW - spiral addressing

KW - eye tremor

KW - non-overlapping convolution

KW - video processing

M3 - Conference contribution

BT - Unknown Host Publication

PB - IEEE

T2 - The International Conference on Image Processing (ICIP)

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