Tracking Multiple Animals in Wildlife Footage

D Tweed; AD Calway

Tracking Multiple Animals in Wildlife Footage

D Tweed, AD Calway

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

11 Citations (Scopus)

Abstract

We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering framework driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.

Translated title of the contribution	Tracking Multiple Animals in Wildlife Footage
Original language	English
Title of host publication	16th International Conference on Pattern Recognition (ICPR 2002), Quebec, August
Editors	R Kasturi, D Laurendeau, C Suen
Publisher	IEEE Computer Society
Pages	20024 - 20027
Number of pages	4
ISBN (Print)	0769516963
Publication status	Published - Aug 2002

Access to Document

http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=1000673

Fingerprint Dive into the research topics of 'Tracking Multiple Animals in Wildlife Footage'. Together they form a unique fingerprint.

Cite this

@inproceedings{ba101423407b4cbc9f17df7087359938,

title = "Tracking Multiple Animals in Wildlife Footage",

abstract = "We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering framework driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential. ",

author = "D Tweed and AD Calway",

year = "2002",

month = aug,

language = "English",

isbn = "0769516963",

pages = "20024 -- 20027",

editor = "R Kasturi and D Laurendeau and C Suen",

booktitle = "16th International Conference on Pattern Recognition (ICPR 2002), Quebec, August",

publisher = "IEEE Computer Society",

address = "United States",

}

TY - GEN

T1 - Tracking Multiple Animals in Wildlife Footage

AU - Tweed, D

AU - Calway, AD

PY - 2002/8

Y1 - 2002/8

N2 - We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering framework driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.

AB - We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering framework driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.

M3 - Conference Contribution (Conference Proceeding)

SN - 0769516963

SP - 20024

EP - 20027

BT - 16th International Conference on Pattern Recognition (ICPR 2002), Quebec, August

A2 - Kasturi, R

A2 - Laurendeau, D

A2 - Suen, C

PB - IEEE Computer Society

ER -