Exploring Multi-Modality in Animal-Centered Computing

Ariel Oren

doi:10.1145/3493842.3493900

Exploring Multi-Modality in Animal-Centered Computing

Ariel Oren

Department of Information Systems

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

Abstract

Automated approaches to animal behavior and emotion recognition and analysis has great potential for expanding scientific knowledge about animals and their interactions with humans, as well as assessment of animal welfare and other applications promoting animal healthcare and well-being. While state-of-the-art AI-based approaches in human behavior and sentiment analysis use multi-modal approaches, most research efforts related to animals have so far addressed one modality at a time: video, audio or sensor data. In this research I aim to fill this gap by exploring multi-modal approaches in the context animal behavior.

Original language	English
Title of host publication	ACI 2021 - 8th International Conference on Animal-Computer Interaction, Proceedings
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450385138
DOIs	https://doi.org/10.1145/3493842.3493900
State	Published - 8 Nov 2021
Event	8th International Conference on Animal-Computer Interaction, ACI 2021 - Virtual, Online, United States Duration: 8 Nov 2021 → 11 Nov 2021

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	8th International Conference on Animal-Computer Interaction, ACI 2021
Country/Territory	United States
City	Virtual, Online
Period	8/11/21 → 11/11/21

Bibliographical note

Publisher Copyright:
© 2021 Owner/Author.

Keywords

Computer vision
Multi-modal data fusion
Signal processing

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3493842.3493900

Cite this

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title = "Exploring Multi-Modality in Animal-Centered Computing",

abstract = "Automated approaches to animal behavior and emotion recognition and analysis has great potential for expanding scientific knowledge about animals and their interactions with humans, as well as assessment of animal welfare and other applications promoting animal healthcare and well-being. While state-of-the-art AI-based approaches in human behavior and sentiment analysis use multi-modal approaches, most research efforts related to animals have so far addressed one modality at a time: video, audio or sensor data. In this research I aim to fill this gap by exploring multi-modal approaches in the context animal behavior.",

keywords = "Computer vision, Multi-modal data fusion, Signal processing",

author = "Ariel Oren",

note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 8th International Conference on Animal-Computer Interaction, ACI 2021 ; Conference date: 08-11-2021 Through 11-11-2021",

year = "2021",

month = nov,

day = "8",

doi = "10.1145/3493842.3493900",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "ACI 2021 - 8th International Conference on Animal-Computer Interaction, Proceedings",

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Oren, A 2021, Exploring Multi-Modality in Animal-Centered Computing. in ACI 2021 - 8th International Conference on Animal-Computer Interaction, Proceedings., 19, ACM International Conference Proceeding Series, Association for Computing Machinery, 8th International Conference on Animal-Computer Interaction, ACI 2021, Virtual, Online, United States, 8/11/21. https://doi.org/10.1145/3493842.3493900

TY - GEN

T1 - Exploring Multi-Modality in Animal-Centered Computing

AU - Oren, Ariel

PY - 2021/11/8

Y1 - 2021/11/8

N2 - Automated approaches to animal behavior and emotion recognition and analysis has great potential for expanding scientific knowledge about animals and their interactions with humans, as well as assessment of animal welfare and other applications promoting animal healthcare and well-being. While state-of-the-art AI-based approaches in human behavior and sentiment analysis use multi-modal approaches, most research efforts related to animals have so far addressed one modality at a time: video, audio or sensor data. In this research I aim to fill this gap by exploring multi-modal approaches in the context animal behavior.

AB - Automated approaches to animal behavior and emotion recognition and analysis has great potential for expanding scientific knowledge about animals and their interactions with humans, as well as assessment of animal welfare and other applications promoting animal healthcare and well-being. While state-of-the-art AI-based approaches in human behavior and sentiment analysis use multi-modal approaches, most research efforts related to animals have so far addressed one modality at a time: video, audio or sensor data. In this research I aim to fill this gap by exploring multi-modal approaches in the context animal behavior.

KW - Computer vision

KW - Multi-modal data fusion

KW - Signal processing

UR - http://www.scopus.com/inward/record.url?scp=85130857661&partnerID=8YFLogxK

U2 - 10.1145/3493842.3493900

DO - 10.1145/3493842.3493900

M3 - Conference contribution

AN - SCOPUS:85130857661

T3 - ACM International Conference Proceeding Series

BT - ACI 2021 - 8th International Conference on Animal-Computer Interaction, Proceedings

PB - Association for Computing Machinery

T2 - 8th International Conference on Animal-Computer Interaction, ACI 2021

Y2 - 8 November 2021 through 11 November 2021

ER -

Exploring Multi-Modality in Animal-Centered Computing

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this