BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages5
Publication statusPublished - 27 Sep 2015
EventThe International Conference on Image Processing (ICIP) - Quebec City, Canada
Duration: 27 Sep 2015 → …

Conference

ConferenceThe International Conference on Image Processing (ICIP)
Period27/09/15 → …

Fingerprint

Image processing
Processing
Pixels
Convolution
Feature extraction

Keywords

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

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",
month = "9",
day = "27",
language = "English",
booktitle = "Unknown Host Publication",

}

Jing, M, Coleman, SA, Bryan, S & McGinnity, TM 2015, BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING. in Unknown Host Publication. The International Conference on Image Processing (ICIP), 27/09/15.

BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING. / Jing, Min; Coleman, SA; Bryan, Scotney; McGinnity, TM.

Unknown Host Publication. 2015.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - BIOLOGICALLY MOTIVATED SPIRAL ARCHITECTURE FOR FAST VIDEO PROCESSING

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

ER -