Analyzing human appearance as a cue for dating images

Tawfiq Salem; Scott Workman; Menghua Zhai; Nathan Jacobs

doi:10.1109/WACV.2016.7477678

Analyzing human appearance as a cue for dating images

Tawfiq Salem, Scott Workman, Menghua Zhai, Nathan Jacobs

Computer Science

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

15 Scopus citations

Abstract

Given an image, we propose to use the appearance of people in the scene to estimate when the picture was taken. There are a wide variety of cues that can be used to address this problem. Most previous work has focused on low-level image features, such as color and vignetting. Recent work on image dating has used more semantic cues, such as the appearance of automobiles and buildings. We extend this line of research by focusing on human appearance. Our approach, based on a deep convolutional neural network, allows us to more deeply explore the relationship between human appearance and time. We find that clothing, hair styles, and glasses can all be informative features. To support our analysis, we have collected a new dataset containing images of people from many high school yearbooks, covering the years 1912-2014. While not a complete solution to the problem of image dating, our results show that human appearance is strongly related to time and that semantic information can be a useful cue.

Original language	English
Title of host publication	2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016
ISBN (Electronic)	9781509006410
DOIs	https://doi.org/10.1109/WACV.2016.7477678
State	Published - May 23 2016
Event	IEEE Winter Conference on Applications of Computer Vision, WACV 2016 - Lake Placid, United States Duration: Mar 7 2016 → Mar 10 2016

Publication series

Name	2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016

Conference

Conference	IEEE Winter Conference on Applications of Computer Vision, WACV 2016
Country/Territory	United States
City	Lake Placid
Period	3/7/16 → 3/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/WACV.2016.7477678

Cite this

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title = "Analyzing human appearance as a cue for dating images",

abstract = "Given an image, we propose to use the appearance of people in the scene to estimate when the picture was taken. There are a wide variety of cues that can be used to address this problem. Most previous work has focused on low-level image features, such as color and vignetting. Recent work on image dating has used more semantic cues, such as the appearance of automobiles and buildings. We extend this line of research by focusing on human appearance. Our approach, based on a deep convolutional neural network, allows us to more deeply explore the relationship between human appearance and time. We find that clothing, hair styles, and glasses can all be informative features. To support our analysis, we have collected a new dataset containing images of people from many high school yearbooks, covering the years 1912-2014. While not a complete solution to the problem of image dating, our results show that human appearance is strongly related to time and that semantic information can be a useful cue.",

author = "Tawfiq Salem and Scott Workman and Menghua Zhai and Nathan Jacobs",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; IEEE Winter Conference on Applications of Computer Vision, WACV 2016 ; Conference date: 07-03-2016 Through 10-03-2016",

year = "2016",

month = may,

day = "23",

doi = "10.1109/WACV.2016.7477678",

language = "English",

series = "2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016",

booktitle = "2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016",

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Salem, T, Workman, S, Zhai, M & Jacobs, N 2016, Analyzing human appearance as a cue for dating images. in 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016., 7477678, 2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016, IEEE Winter Conference on Applications of Computer Vision, WACV 2016, Lake Placid, United States, 3/7/16. https://doi.org/10.1109/WACV.2016.7477678

Analyzing human appearance as a cue for dating images. / Salem, Tawfiq; Workman, Scott; Zhai, Menghua et al.
2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016. 2016. 7477678 (2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016).

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

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AU - Workman, Scott

AU - Zhai, Menghua

AU - Jacobs, Nathan

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N2 - Given an image, we propose to use the appearance of people in the scene to estimate when the picture was taken. There are a wide variety of cues that can be used to address this problem. Most previous work has focused on low-level image features, such as color and vignetting. Recent work on image dating has used more semantic cues, such as the appearance of automobiles and buildings. We extend this line of research by focusing on human appearance. Our approach, based on a deep convolutional neural network, allows us to more deeply explore the relationship between human appearance and time. We find that clothing, hair styles, and glasses can all be informative features. To support our analysis, we have collected a new dataset containing images of people from many high school yearbooks, covering the years 1912-2014. While not a complete solution to the problem of image dating, our results show that human appearance is strongly related to time and that semantic information can be a useful cue.

AB - Given an image, we propose to use the appearance of people in the scene to estimate when the picture was taken. There are a wide variety of cues that can be used to address this problem. Most previous work has focused on low-level image features, such as color and vignetting. Recent work on image dating has used more semantic cues, such as the appearance of automobiles and buildings. We extend this line of research by focusing on human appearance. Our approach, based on a deep convolutional neural network, allows us to more deeply explore the relationship between human appearance and time. We find that clothing, hair styles, and glasses can all be informative features. To support our analysis, we have collected a new dataset containing images of people from many high school yearbooks, covering the years 1912-2014. While not a complete solution to the problem of image dating, our results show that human appearance is strongly related to time and that semantic information can be a useful cue.

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M3 - Conference contribution

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Analyzing human appearance as a cue for dating images

Abstract

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Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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