FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR

Research output: Contribution to conferencePaper

Abstract

This paper presents an efficient approach to corner detection in images using a spiral addressing scheme in conjunction with simulated, biological involuntary eye movements. As part of this approach, a combined gradient detection and smoothing operation is used to quickly obtain a feature representation that can be used with a standard ‘cornerness’ measure. A computationally efficient use of the spiral address scheme to apply further processing operations such as non-maximum suppression is demonstrated. Comparative evaluation of three corner detection methods is presented and results demonstrate significantly faster processing times than other well-known corner detection methods.

Conference

ConferenceInternational Conference on Artificial Intelligence and Pattern Recognition
Abbreviated titleAIPR 2018
CountryChina
City Beijing
Period18/08/1820/08/18
Internet address

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Eye movements
Processing

Cite this

Fegan, J., Coleman, S., Kerr, D., & Scotney, B. (Accepted/In press). FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.
Fegan, John ; Coleman, Sonya ; Kerr, Dermot ; Scotney, Bryan. / FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.5 p.
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title = "FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR",
abstract = "This paper presents an efficient approach to corner detection in images using a spiral addressing scheme in conjunction with simulated, biological involuntary eye movements. As part of this approach, a combined gradient detection and smoothing operation is used to quickly obtain a feature representation that can be used with a standard ‘cornerness’ measure. A computationally efficient use of the spiral address scheme to apply further processing operations such as non-maximum suppression is demonstrated. Comparative evaluation of three corner detection methods is presented and results demonstrate significantly faster processing times than other well-known corner detection methods.",
author = "John Fegan and Sonya Coleman and Dermot Kerr and Bryan Scotney",
year = "2018",
month = "6",
day = "20",
language = "English",
note = "International Conference on Artificial Intelligence and Pattern Recognition , AIPR 2018 ; Conference date: 18-08-2018 Through 20-08-2018",
url = "http://www.aipr.net",

}

Fegan, J, Coleman, S, Kerr, D & Scotney, B 2018, 'FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR' Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China, 18/08/18 - 20/08/18, .

FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR. / Fegan, John; Coleman, Sonya; Kerr, Dermot; Scotney, Bryan.

2018. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.

Research output: Contribution to conferencePaper

TY - CONF

T1 - FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR

AU - Fegan, John

AU - Coleman, Sonya

AU - Kerr, Dermot

AU - Scotney, Bryan

PY - 2018/6/20

Y1 - 2018/6/20

N2 - This paper presents an efficient approach to corner detection in images using a spiral addressing scheme in conjunction with simulated, biological involuntary eye movements. As part of this approach, a combined gradient detection and smoothing operation is used to quickly obtain a feature representation that can be used with a standard ‘cornerness’ measure. A computationally efficient use of the spiral address scheme to apply further processing operations such as non-maximum suppression is demonstrated. Comparative evaluation of three corner detection methods is presented and results demonstrate significantly faster processing times than other well-known corner detection methods.

AB - This paper presents an efficient approach to corner detection in images using a spiral addressing scheme in conjunction with simulated, biological involuntary eye movements. As part of this approach, a combined gradient detection and smoothing operation is used to quickly obtain a feature representation that can be used with a standard ‘cornerness’ measure. A computationally efficient use of the spiral address scheme to apply further processing operations such as non-maximum suppression is demonstrated. Comparative evaluation of three corner detection methods is presented and results demonstrate significantly faster processing times than other well-known corner detection methods.

M3 - Paper

ER -

Fegan J, Coleman S, Kerr D, Scotney B. FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR. 2018. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.