Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic

Tanvi Banerjee; James M. Keller; Marjorie Skubie

doi:10.1109/FUZZ-IEEE.2014.6891647

Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic

Tanvi Banerjee, James M. Keller, Marjorie Skubie

Computer Science and Engineering

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

Abstract

Complex activities such as instrumental activities of daily living (IADLs) can be identified by creating a hierarchical model of fuzzy rules. In this work, we present a framework to model a specific IADL – “making the bed”. For this activity recognition, the need for a three level Fuzzy Inference System (FIS) model is shown. Simple features such as bounding box parameters were extracted from the foreground images and combined with 3D features extracted from the Kinect depth data. This was then fed as input to the three layered FIS for further analysis. Data collected from several participants were tested and evaluated. Such a framework can be used to model several other IADLS as well as basic activities of daily living (ADLs). Analysis of ADLs can be used to compare daily patterns in older adults to measure changes in behavior. This can then be used to predict health changes to assist older adults in leading independent lifestyles for longer time periods.

Original language	American English
Title of host publication	2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	IEEE
Pages	540-547
Number of pages	8
ISBN (Electronic)	978-1-4799-2072-3, 978-1-4799-2073-0
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2014.6891647
State	Published - Sep 8 2014
Event	2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing, China Duration: Jul 6 2014 → Jul 11 2014

Conference

Conference	2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
Country/Territory	China
City	Beijing
Period	7/6/14 → 7/11/14

ASJC Scopus Subject Areas

Software
Theoretical Computer Science
Artificial Intelligence
Applied Mathematics

Keywords

Activities of Daily Living
Depth Image
Fuzzy Rules
Machine Learning

Disciplines

Bioinformatics
Communication Technology and New Media
Databases and Information Systems
OS and Networks
Science and Technology Studies

Access to Document

10.1109/FUZZ-IEEE.2014.6891647License: Unspecified

Cite this

Banerjee, T, Keller, JM & Skubie, M 2014, Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic. in 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)., 6891647, IEEE, pp. 540-547, 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014, Beijing, China, 7/6/14. https://doi.org/10.1109/FUZZ-IEEE.2014.6891647

@inproceedings{13b1d80eb57a43d18907cdb23917b4d7,

title = "Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic",

abstract = " Complex activities such as instrumental activities of daily living (IADLs) can be identified by creating a hierarchical model of fuzzy rules. In this work, we present a framework to model a specific IADL – “making the bed”. For this activity recognition, the need for a three level Fuzzy Inference System (FIS) model is shown. Simple features such as bounding box parameters were extracted from the foreground images and combined with 3D features extracted from the Kinect depth data. This was then fed as input to the three layered FIS for further analysis. Data collected from several participants were tested and evaluated. Such a framework can be used to model several other IADLS as well as basic activities of daily living (ADLs). Analysis of ADLs can be used to compare daily patterns in older adults to measure changes in behavior. This can then be used to predict health changes to assist older adults in leading independent lifestyles for longer time periods.",

keywords = "Activities of Daily Living, Depth Image, Fuzzy Rules, Machine Learning",

author = "Tanvi Banerjee and Keller, {James M.} and Marjorie Skubie",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 ; Conference date: 06-07-2014 Through 11-07-2014",

year = "2014",

month = sep,

day = "8",

doi = "10.1109/FUZZ-IEEE.2014.6891647",

language = "American English",

pages = "540--547",

booktitle = "2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",

publisher = "IEEE",

}

TY - GEN

T1 - Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic

AU - Banerjee, Tanvi

AU - Keller, James M.

AU - Skubie, Marjorie

PY - 2014/9/8

Y1 - 2014/9/8

N2 - Complex activities such as instrumental activities of daily living (IADLs) can be identified by creating a hierarchical model of fuzzy rules. In this work, we present a framework to model a specific IADL – “making the bed”. For this activity recognition, the need for a three level Fuzzy Inference System (FIS) model is shown. Simple features such as bounding box parameters were extracted from the foreground images and combined with 3D features extracted from the Kinect depth data. This was then fed as input to the three layered FIS for further analysis. Data collected from several participants were tested and evaluated. Such a framework can be used to model several other IADLS as well as basic activities of daily living (ADLs). Analysis of ADLs can be used to compare daily patterns in older adults to measure changes in behavior. This can then be used to predict health changes to assist older adults in leading independent lifestyles for longer time periods.

AB - Complex activities such as instrumental activities of daily living (IADLs) can be identified by creating a hierarchical model of fuzzy rules. In this work, we present a framework to model a specific IADL – “making the bed”. For this activity recognition, the need for a three level Fuzzy Inference System (FIS) model is shown. Simple features such as bounding box parameters were extracted from the foreground images and combined with 3D features extracted from the Kinect depth data. This was then fed as input to the three layered FIS for further analysis. Data collected from several participants were tested and evaluated. Such a framework can be used to model several other IADLS as well as basic activities of daily living (ADLs). Analysis of ADLs can be used to compare daily patterns in older adults to measure changes in behavior. This can then be used to predict health changes to assist older adults in leading independent lifestyles for longer time periods.

KW - Activities of Daily Living

KW - Depth Image

KW - Fuzzy Rules

KW - Machine Learning

UR - http://www.scopus.com/inward/record.url?scp=84912523214&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84912523214&partnerID=8YFLogxK

UR - https://corescholar.libraries.wright.edu/knoesis/1108

U2 - 10.1109/FUZZ-IEEE.2014.6891647

DO - 10.1109/FUZZ-IEEE.2014.6891647

M3 - Conference contribution

SP - 540

EP - 547

BT - 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

PB - IEEE

T2 - 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014

Y2 - 6 July 2014 through 11 July 2014

ER -

Building a Framework for Recognition of Activities of Daily Living from Depth Images using Fuzzy Logic

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

Other files and links

Cite this