Visual analytics for cheetah behaviour analysis

Karsten Klein; Sabrina Jaeger; Jörg Melzheimer; Bettina Wachter; Heribert Hofer; Artur Baltabayev; Falk Schreiber

doi:10.1145/3356422.3356435

Visual analytics for cheetah behaviour analysis

Karsten Klein, Sabrina Jaeger, Jörg Melzheimer, Bettina Wachter, Heribert Hofer, Artur Baltabayev, Falk Schreiber

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

2 Citations (Scopus)

Abstract

Recent advances in tracking technology allow biologists to collect large amounts of movement data for a variety of species. Analysis of the collected data supports research on animal behaviour, influence of impact factors such as climate change and human intervention, as well as conservation programs. Analysis of the movement data is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, e.g. for the detection of behavioural patterns, and human inspection, e.g. for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments.

Original language	English
Title of host publication	Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019
Editors	Changbo Wang, Michael Burch, Michael Krone
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Number of pages	8
ISBN (Electronic)	9781450376266
DOIs	https://doi.org/10.1145/3356422.3356435
Publication status	Published - 2019
Externally published	Yes
Event	International Symposium on Visual Information Communication and Interaction 2019 - Shanghai, China Duration: 20 Sep 2019 → 22 Sep 2019 Conference number: 12th http://vinci-conf.org/2019/ (Website) https://dl.acm.org/doi/proceedings/10.1145/3356422 (Proceedings)

Conference

Conference	International Symposium on Visual Information Communication and Interaction 2019
Abbreviated title	VINCI 2019
Country/Territory	China
City	Shanghai
Period	20/09/19 → 22/09/19
Internet address	http://vinci-conf.org/2019/ (Website) https://dl.acm.org/doi/proceedings/10.1145/3356422 (Proceedings)

Keywords

Animal movement
Data visualisation
Machine learning
Visual analytics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3356422.3356435

Cite this

Klein, K., Jaeger, S., Melzheimer, J., Wachter, B., Hofer, H., Baltabayev, A., & Schreiber, F. (2019). Visual analytics for cheetah behaviour analysis. In C. Wang, M. Burch, & M. Krone (Eds.), Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019 [3356435] Association for Computing Machinery (ACM). https://doi.org/10.1145/3356422.3356435

Klein, Karsten ; Jaeger, Sabrina ; Melzheimer, Jörg ; Wachter, Bettina ; Hofer, Heribert ; Baltabayev, Artur ; Schreiber, Falk. / Visual analytics for cheetah behaviour analysis. Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019. editor / Changbo Wang ; Michael Burch ; Michael Krone. New York NY USA : Association for Computing Machinery (ACM), 2019.

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title = "Visual analytics for cheetah behaviour analysis",

abstract = "Recent advances in tracking technology allow biologists to collect large amounts of movement data for a variety of species. Analysis of the collected data supports research on animal behaviour, influence of impact factors such as climate change and human intervention, as well as conservation programs. Analysis of the movement data is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, e.g. for the detection of behavioural patterns, and human inspection, e.g. for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments.",

keywords = "Animal movement, Data visualisation, Machine learning, Visual analytics",

author = "Karsten Klein and Sabrina Jaeger and J{\"o}rg Melzheimer and Bettina Wachter and Heribert Hofer and Artur Baltabayev and Falk Schreiber",

year = "2019",

doi = "10.1145/3356422.3356435",

language = "English",

editor = "Wang, {Changbo } and Burch, {Michael } and Krone, {Michael }",

booktitle = "Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "International Symposium on Visual Information Communication and Interaction 2019, VINCI 2019 ; Conference date: 20-09-2019 Through 22-09-2019",

url = "http://vinci-conf.org/2019/, https://dl.acm.org/doi/proceedings/10.1145/3356422",

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Klein, K, Jaeger, S, Melzheimer, J, Wachter, B, Hofer, H, Baltabayev, A & Schreiber, F 2019, Visual analytics for cheetah behaviour analysis. in C Wang, M Burch & M Krone (eds), Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019., 3356435, Association for Computing Machinery (ACM), New York NY USA, International Symposium on Visual Information Communication and Interaction 2019, Shanghai, China, 20/09/19. https://doi.org/10.1145/3356422.3356435

Visual analytics for cheetah behaviour analysis. / Klein, Karsten; Jaeger, Sabrina; Melzheimer, Jörg; Wachter, Bettina; Hofer, Heribert; Baltabayev, Artur; Schreiber, Falk.

Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019. ed. / Changbo Wang; Michael Burch; Michael Krone. New York NY USA : Association for Computing Machinery (ACM), 2019. 3356435.

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

TY - GEN

T1 - Visual analytics for cheetah behaviour analysis

AU - Klein, Karsten

AU - Jaeger, Sabrina

AU - Melzheimer, Jörg

AU - Wachter, Bettina

AU - Hofer, Heribert

AU - Baltabayev, Artur

AU - Schreiber, Falk

N1 - Conference code: 12th

PY - 2019

Y1 - 2019

N2 - Recent advances in tracking technology allow biologists to collect large amounts of movement data for a variety of species. Analysis of the collected data supports research on animal behaviour, influence of impact factors such as climate change and human intervention, as well as conservation programs. Analysis of the movement data is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, e.g. for the detection of behavioural patterns, and human inspection, e.g. for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments.

AB - Recent advances in tracking technology allow biologists to collect large amounts of movement data for a variety of species. Analysis of the collected data supports research on animal behaviour, influence of impact factors such as climate change and human intervention, as well as conservation programs. Analysis of the movement data is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, e.g. for the detection of behavioural patterns, and human inspection, e.g. for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments.

KW - Animal movement

KW - Data visualisation

KW - Machine learning

KW - Visual analytics

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U2 - 10.1145/3356422.3356435

DO - 10.1145/3356422.3356435

M3 - Conference Paper

AN - SCOPUS:85076817874

BT - Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019

A2 - Wang, Changbo

A2 - Burch, Michael

A2 - Krone, Michael

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - International Symposium on Visual Information Communication and Interaction 2019

Y2 - 20 September 2019 through 22 September 2019

ER -

Klein K, Jaeger S, Melzheimer J, Wachter B, Hofer H, Baltabayev A et al. Visual analytics for cheetah behaviour analysis. In Wang C, Burch M, Krone M, editors, Proceedings of the 12th International Symposium on Visual Information Communication and Interaction, VINCI 2019. New York NY USA: Association for Computing Machinery (ACM). 2019. 3356435 https://doi.org/10.1145/3356422.3356435

Visual analytics for cheetah behaviour analysis

Abstract

Conference

Keywords

UN SDGs

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