Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you

Masakazu Iwamura; Kai Kunze; Yuya Kato; Yuzuko Utsumi; Koichi Kise

doi:10.1145/2582051.2582083

Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you

Masakazu Iwamura, Kai Kunze, Yuya Kato, Yuzuko Utsumi, Koichi Kise

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

10 Citations (Scopus)

Abstract

This paper presents a perceived real-time system for memory augmentation. We propose a realistic approach to realize a memory assistance system, focusing on retrieving the person in front of you. The proposed system is capable of fully automatic indexing and is scalable in the database size. We utilize face recognition to show the user previous encounters with the person they are currently looking at. The system works fast (under 200 ms, perceived real time) with a decent database size (45 videos of 24 people). We also provide evidence in terms of an online questionnaire that our proposed memory augmentation system is useful and would be worn by most of the participants if it can be implemented in an unobtrusive way.

Original language	English
Title of host publication	Proceedings of the 5th Augmented Human International Conference, AH 2014
Publisher	Association for Computing Machinery
ISBN (Print)	9781450327619
DOIs	https://doi.org/10.1145/2582051.2582083
Publication status	Published - 2014
Externally published	Yes
Event	5th Augmented Human International Conference, AH 2014 - Kobe, Japan Duration: 2014 Mar 7 → 2014 Mar 8

Publication series

Name	ACM International Conference Proceeding Series

Other

Other	5th Augmented Human International Conference, AH 2014
Country/Territory	Japan
City	Kobe
Period	14/3/7 → 14/3/8

Keywords

Face recognition
Memory assistance system
Memory augmentation
Wearable

ASJC Scopus subject areas

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

Access to Document

10.1145/2582051.2582083

Cite this

Iwamura, M., Kunze, K., Kato, Y., Utsumi, Y., & Kise, K. (2014). Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you. In Proceedings of the 5th Augmented Human International Conference, AH 2014 [a32] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2582051.2582083

Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you. / Iwamura, Masakazu; Kunze, Kai; Kato, Yuya; Utsumi, Yuzuko; Kise, Koichi.

Proceedings of the 5th Augmented Human International Conference, AH 2014. Association for Computing Machinery, 2014. a32 (ACM International Conference Proceeding Series).

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

Iwamura, M, Kunze, K, Kato, Y, Utsumi, Y & Kise, K 2014, Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you. in Proceedings of the 5th Augmented Human International Conference, AH 2014., a32, ACM International Conference Proceeding Series, Association for Computing Machinery, 5th Augmented Human International Conference, AH 2014, Kobe, Japan, 14/3/7. https://doi.org/10.1145/2582051.2582083

@inproceedings{e740072890e74310bbac4b89e6fc3d7b,

title = "Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you",

abstract = "This paper presents a perceived real-time system for memory augmentation. We propose a realistic approach to realize a memory assistance system, focusing on retrieving the person in front of you. The proposed system is capable of fully automatic indexing and is scalable in the database size. We utilize face recognition to show the user previous encounters with the person they are currently looking at. The system works fast (under 200 ms, perceived real time) with a decent database size (45 videos of 24 people). We also provide evidence in terms of an online questionnaire that our proposed memory augmentation system is useful and would be worn by most of the participants if it can be implemented in an unobtrusive way.",

keywords = "Face recognition, Memory assistance system, Memory augmentation, Wearable",

author = "Masakazu Iwamura and Kai Kunze and Yuya Kato and Yuzuko Utsumi and Koichi Kise",

year = "2014",

doi = "10.1145/2582051.2582083",

language = "English",

isbn = "9781450327619",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "Proceedings of the 5th Augmented Human International Conference, AH 2014",

}

TY - GEN

T1 - Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you

AU - Iwamura, Masakazu

AU - Kunze, Kai

AU - Kato, Yuya

AU - Utsumi, Yuzuko

AU - Kise, Koichi

PY - 2014

Y1 - 2014

N2 - This paper presents a perceived real-time system for memory augmentation. We propose a realistic approach to realize a memory assistance system, focusing on retrieving the person in front of you. The proposed system is capable of fully automatic indexing and is scalable in the database size. We utilize face recognition to show the user previous encounters with the person they are currently looking at. The system works fast (under 200 ms, perceived real time) with a decent database size (45 videos of 24 people). We also provide evidence in terms of an online questionnaire that our proposed memory augmentation system is useful and would be worn by most of the participants if it can be implemented in an unobtrusive way.

AB - This paper presents a perceived real-time system for memory augmentation. We propose a realistic approach to realize a memory assistance system, focusing on retrieving the person in front of you. The proposed system is capable of fully automatic indexing and is scalable in the database size. We utilize face recognition to show the user previous encounters with the person they are currently looking at. The system works fast (under 200 ms, perceived real time) with a decent database size (45 videos of 24 people). We also provide evidence in terms of an online questionnaire that our proposed memory augmentation system is useful and would be worn by most of the participants if it can be implemented in an unobtrusive way.

KW - Face recognition

KW - Memory assistance system

KW - Memory augmentation

KW - Wearable

UR - http://www.scopus.com/inward/record.url?scp=84899849951&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84899849951&partnerID=8YFLogxK

U2 - 10.1145/2582051.2582083

DO - 10.1145/2582051.2582083

M3 - Conference contribution

AN - SCOPUS:84899849951

SN - 9781450327619

T3 - ACM International Conference Proceeding Series

BT - Proceedings of the 5th Augmented Human International Conference, AH 2014

PB - Association for Computing Machinery

T2 - 5th Augmented Human International Conference, AH 2014

Y2 - 7 March 2014 through 8 March 2014

ER -

Haven't we met before? - A realistic memory assistance system to remind you of the person in front of you

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this