What Will Your Future Child Look Like? Modeling and Synthesis of Hereditary Patterns of Facial Dynamics

Itir Önal Ertugrul, Hamdi Dibeklioglu

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

Analysis of kinship from facial images or videos is an important problem. Prior machine learning and computer vision studies approach kinship analysis as a verification or recognition task. In this paper, first time in the literature, we propose a kinship synthesis framework, which generates smile videos of (probable) children from the smile videos of parents. While the appearance of a child's smile is learned using a convolutional encoder-decoder network, another neural network models the dynamics of the corresponding smile. The smile video of the estimated child is synthesized by the combined use of appearance and dynamics models. In order to validate our results, we perform kinship verification experiments using videos of real parents and estimated children generated by our framework. The results show that generated videos of children achieve higher correct verification rates than those of real children. Our results also indicate that the use of generated videos together with the real ones in the training of kinship verification models, increases the accuracy, suggesting that such videos can be used as a synthetic dataset.

Original languageEnglish
Title of host publication2017 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017)
EditorsR. Bilof
Place of PublicationPiscataway
PublisherIEEE
Pages33-40
Number of pages8
ISBN (Electronic)9781509040230
ISBN (Print)978-1-5090-4024-7
DOIs
Publication statusPublished - 2017
Event12th IEEE International Conference on Automatic Face and Gesture Recognition: 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017 - Washington, United States
Duration: 30 May 20173 Jun 2017

Conference

Conference12th IEEE International Conference on Automatic Face and Gesture Recognition
Abbreviated titleFG 2017
CountryUnited States
CityWashington
Period30/05/173/06/17

Keywords

  • Videos
  • Face
  • Neural networks
  • Eyebrows
  • Nose
  • Mouth
  • Time series analysis

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