Human shape recognition from snakes using neural networks

Ken Tabb; N. Davey; S. George; R.G. Adams

doi:10.1109/ICCIMA.1999.798545

Human shape recognition from snakes using neural networks

Ken Tabb
, N. Davey
, S. George
, R.G. Adams

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

6 Citations (Scopus)

85 Downloads (Pure)

Abstract

This paper documents experiments which have been carried out with several neural network systems designed to categorise pedestrian shapes from non-pedestrian shapes. Active Contour models (‘Snakes’) [1] have been used to obtain contours of pedestrians as they move around the visual field. Neural networks have then been trained on representations of these relaxed snakes. The neural network systems developed can successfully discriminate these contours based upon whether they are ‘pedestrian’ in shape or not. Results are presented along with a discussion of some of the system’s possible applications.

Original language	English
Title of host publication	In: Procs 3rd Int Conf on Computational Intelligence and Multimedia Applications (ICCIMA'99)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	292-296
ISBN (Print)	0-7695-0300-4
DOIs	https://doi.org/10.1109/ICCIMA.1999.798545
Publication status	Published - 1999

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@inproceedings{2266acd60930434e9d8d45ed619b7641,

title = "Human shape recognition from snakes using neural networks",

abstract = "This paper documents experiments which have been carried out with several neural network systems designed to categorise pedestrian shapes from non-pedestrian shapes. Active Contour models ({\textquoteleft}Snakes{\textquoteright}) [1] have been used to obtain contours of pedestrians as they move around the visual field. Neural networks have then been trained on representations of these relaxed snakes. The neural network systems developed can successfully discriminate these contours based upon whether they are {\textquoteleft}pedestrian{\textquoteright} in shape or not. Results are presented along with a discussion of some of the system{\textquoteright}s possible applications.",

author = "Ken Tabb and N. Davey and S. George and R.G. Adams",

note = "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. --DOI : 10.1109/ICCIMA.1999.798545",

year = "1999",

doi = "10.1109/ICCIMA.1999.798545",

language = "English",

isbn = "0-7695-0300-4",

pages = "292--296",

booktitle = "In: Procs 3rd Int Conf on Computational Intelligence and Multimedia Applications (ICCIMA'99)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

TY - GEN

T1 - Human shape recognition from snakes using neural networks

AU - Tabb, Ken

AU - Davey, N.

AU - George, S.

AU - Adams, R.G.

N1 - This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. --DOI : 10.1109/ICCIMA.1999.798545

PY - 1999

Y1 - 1999

N2 - This paper documents experiments which have been carried out with several neural network systems designed to categorise pedestrian shapes from non-pedestrian shapes. Active Contour models (‘Snakes’) [1] have been used to obtain contours of pedestrians as they move around the visual field. Neural networks have then been trained on representations of these relaxed snakes. The neural network systems developed can successfully discriminate these contours based upon whether they are ‘pedestrian’ in shape or not. Results are presented along with a discussion of some of the system’s possible applications.

AB - This paper documents experiments which have been carried out with several neural network systems designed to categorise pedestrian shapes from non-pedestrian shapes. Active Contour models (‘Snakes’) [1] have been used to obtain contours of pedestrians as they move around the visual field. Neural networks have then been trained on representations of these relaxed snakes. The neural network systems developed can successfully discriminate these contours based upon whether they are ‘pedestrian’ in shape or not. Results are presented along with a discussion of some of the system’s possible applications.

U2 - 10.1109/ICCIMA.1999.798545

DO - 10.1109/ICCIMA.1999.798545

M3 - Conference contribution

SN - 0-7695-0300-4

SP - 292

EP - 296

BT - In: Procs 3rd Int Conf on Computational Intelligence and Multimedia Applications (ICCIMA'99)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Human shape recognition from snakes using neural networks

Abstract

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