iMCD lifelogging data : observed faces and persons

UBDC staff developed methods to analyse lifelogging image data collected within the Integrated Multimedia City Data (iMCD) project to study people's isolation level in the city.

To this end, they use the image set as an attempt to group people with similar social state and behaviour based on the number of faces and number of people they are surrounded by in their everyday life.

Using Computer Vision techniques, UBDC staff detected the number of people and the number of faces on each of the participants’ images. The result of the process was a set of features/characteristics for each participant, among which were the percentage of images they had with nobody, 1 person, etc and also with 1 face, 2 faces, etc. The next step was to cluster the participants based on the above feature space, namely create groups of people with similar social activity. After validation and experimentation, there were three clusters (groups) of people with similar social behaviour: a) low social activity, b) medium social activity, c) high social activity.

The result of this process was to enrich UBDC's existing data of participants with an additional feature, their social group, based on additional survey data.

Access and Restrictions

Data available for non-commercial academic research under UBDC’s End User Licence Agreement. Permitted to use for teaching purposes.

Cite this as

Urban Big Data Centre (2023). iMCD lifelogging data : observed faces and persons [Data set]. University of Glasgow. https://doi.org/10.20394/lvxtxtdb
Retrieved: 15:17 07 Feb 2025 (UTC)

Additional Info

Title iMCD lifelogging data : observed faces and persons
Alternative title
URL imcd-lifelogging-data-observed-faces-and-persons
Description

UBDC staff developed methods to analyse lifelogging image data collected within the Integrated Multimedia City Data (iMCD) project to study people's isolation level in the city.

To this end, they use the image set as an attempt to group people with similar social state and behaviour based on the number of faces and number of people they are surrounded by in their everyday life.

Using Computer Vision techniques, UBDC staff detected the number of people and the number of faces on each of the participants’ images. The result of the process was a set of features/characteristics for each participant, among which were the percentage of images they had with nobody, 1 person, etc and also with 1 face, 2 faces, etc. The next step was to cluster the participants based on the above feature space, namely create groups of people with similar social activity. After validation and experimentation, there were three clusters (groups) of people with similar social behaviour: a) low social activity, b) medium social activity, c) high social activity.

The result of this process was to enrich UBDC's existing data of participants with an additional feature, their social group, based on additional survey data.

Access and Restrictions

Data available for non-commercial academic research under UBDC’s End User Licence Agreement. Permitted to use for teaching purposes.

Content

The data consists of a csv file, which includes the lifelogger's unique ID and the number or percentage of images with persons or faces identified and a corresponding data dictionary file.

Subjects
Topics
Dataset Citation Urban Big Data Centre. Economic and Social Research Council. iMCD Project: Lifelogging Data, 2015 [data collection]. University of Glasgow - Urban Big Data Centre. 
Time Period Coverage 15/04/2015-21/11/2015
Geographical Coverage Glasgow
Spatial Units
Observation Units images
Resource Type Dataset
Data Format numeric
Weighting
Method of Collection

using wearable technology

Collection Status closed-completed
Dataset Aggregation
Data Owner Urban Big Data Centre
Data Owner Url https://www.ubdc.ac.uk/
License other-closed
Licence Specifics

For non-commercial academic research use only.

Provider b2ba2219-ff6c-461a-a746-e762ef7600fd
Version
Dataset Available
Dataset Closed
Dataset Valid
Dataset Updating Frequency
Dataset Next Version Due
Date Published 2023-08-30
Date of Fieldwork
Dataset File Type
Dataset File Size 1.5 MB
Dataset Creation Date
Dataset Access Restrictions Safeguarded Dataset
Metadata Created Date 2023-08-30
Metadata Created Institution Urban Big Data Centre
Dataset Fields (1)
Field Name:
Description:
Type: