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Estimating heights from photo collections: a data-driven approach

Published: 01 October 2014 Publication History

Abstract

A photo can potentially reveal a tremendous amount of information about an individual, including the individual's height, weight, gender, ethnicity, hair color, skin condition, interests, and wealth. A {\em photo collection} -- a set of inter-related photos including photos of many people appearing in two or more photos -- could potentially reveal a more vivid picture of the individuals in the collection.
In this paper we consider the problem of estimating the heights of all the users in a photo collection, such as a collection of photos from a social network. The main ideas in our methodology are (i) for each individual photo, estimate the height differences among the people standing in the photo, (ii) from the photo collection, create a people graph, and combine this graph with the height difference estimates from the individual photos to generate height difference estimates among all the people in the collection, (iii) then use these height difference estimates, as well as an a priori distribution, to estimate the heights of all the people in the photo collection. Because many people will appear in multiple photos across the collection, height-difference estimates can be chained together, potentially reducing the errors in the estimates. To this end, we formulate a Maximum Likelihood Estimation (MLE) problem, which we show can be easily solved as a quadratic programming problem. Intuitively, this data-driven approach will improve as the number of photos and people in the collection increases. We apply the technique to estimating the heights of over 400 movie stars in the IMDb database and of about 30 graduate students.

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  • (2024)Reference-Based Human Height Estimation2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776415(571-578)Online publication date: 26-Sep-2024
  • (2022)Enhancement of human 3D pose estimation using a novel concept of depth prediction with pose alignment from a single 2D imageComputers and Graphics10.1016/j.cag.2022.07.021107:C(172-185)Online publication date: 1-Oct-2022
  • (2022)Effect of Gender, Pose and Camera Distance on Human Body Dimensions EstimationImage Analysis and Processing. ICIAP 2022 Workshops10.1007/978-3-031-13324-4_16(179-190)Online publication date: 23-May-2022
  • Show More Cited By

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cover image ACM Conferences
COSN '14: Proceedings of the second ACM conference on Online social networks
October 2014
288 pages
ISBN:9781450331982
DOI:10.1145/2660460
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 October 2014

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Author Tags

  1. concept extraction
  2. height estimate
  3. image processing
  4. maximum likelihood estimation
  5. people graph
  6. photo collection
  7. privacy

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COSN'14
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COSN'14: Conference on Online Social Networks
October 1 - 2, 2014
Dublin, Ireland

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COSN '14 Paper Acceptance Rate 25 of 87 submissions, 29%;
Overall Acceptance Rate 69 of 307 submissions, 22%

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Cited By

View all
  • (2024)Reference-Based Human Height Estimation2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776415(571-578)Online publication date: 26-Sep-2024
  • (2022)Enhancement of human 3D pose estimation using a novel concept of depth prediction with pose alignment from a single 2D imageComputers and Graphics10.1016/j.cag.2022.07.021107:C(172-185)Online publication date: 1-Oct-2022
  • (2022)Effect of Gender, Pose and Camera Distance on Human Body Dimensions EstimationImage Analysis and Processing. ICIAP 2022 Workshops10.1007/978-3-031-13324-4_16(179-190)Online publication date: 23-May-2022
  • (2021)Single Image Human Proxemics Estimation for Visual Social Distancing2021 IEEE Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV48630.2021.00283(2784-2794)Online publication date: Jan-2021
  • (2020)Human biases in body measurement estimationEPJ Data Science10.1140/epjds/s13688-020-00250-x9:1Online publication date: 27-Oct-2020
  • (2020)Height and Weight Estimation from Unconstrained ImagesICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP40776.2020.9053363(2298-2302)Online publication date: May-2020
  • (2020)The Visual Social Distancing ProblemIEEE Access10.1109/ACCESS.2020.30083708(126876-126886)Online publication date: 2020
  • (2019)What Face and Body Shapes Can Tell Us About Height2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)10.1109/ICCVW.2019.00226(1819-1827)Online publication date: Oct-2019
  • (2019)Gravity as a Reference for Estimating a Person’s Height From Video2019 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV.2019.00866(8568-8576)Online publication date: Oct-2019
  • (2015)Dawn of the Selfie EraProceedings of the 2015 ACM on Conference on Online Social Networks10.1145/2817946.2817948(221-231)Online publication date: 2-Nov-2015

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