The familiar: a living diary and companion

Authors:
Brian Clarkson;Kenji Mase;Alex Pentland
Affiliations:
MIT Media Laboratory, Cambridge, MA;ATR Media Integration & Communications Research Laboratories, Kyoto, Japan;MIT Media Laboratory, Cambridge, MA
Venue:
CHI '01 Extended Abstracts on Human Factors in Computing Systems
Year:
2001

Citing 1
Cited 9

Unsupervised clustering of ambulatory audio and video

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06

ComicDiary: Representing Individual Experiences in a Comics Style

UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Musically Expressive Doll in Face-to-Face Communication

ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
RSS as a distribution medium for geo-spatial hypermedia

Proceedings of the sixteenth ACM conference on Hypertext and hypermedia
Ubiquitous Experience Media

IEEE MultiMedia
InSense: Interest-Based Life Logging

IEEE MultiMedia
Informing augmented memory system design through autobiographical memory theory

Personal and Ubiquitous Computing
Easy Living in the Virtual World: A Noble Approach to Integrate Real World Activities to Virtual Worlds

WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Unconscious emotions: quantifying and logging something we are not aware of

Personal and Ubiquitous Computing
Building health persona from personal data streams

Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a perceptual system, called the Familiar, that could allow a user to collect his/her memories over their lifetime into a continually growing and adapting multimedia diary. The Familiar uses the natural patterns in sensor readings from a camera, microphone, and accelerometers, to find the recurring patterns of similarity and dissimilarity in the user's activities and uses this information to intelligently structure the user's sensor data and associated memorabilia.