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2017 Fiscal Year Research-status Report

Real World Heart Rate Estimation from Video

Research Project

Project/Area Number 17K12709
Research InstitutionSaitama University

Principal Investigator

Lam Antony  埼玉大学, 理工学研究科, 助教 (50744124)

Project Period (FY) 2017-04-01 – 2019-03-31
Keywordsvideo ppg / computer vision / heart rate / cardiac estimation / remote measurement
Outline of Annual Research Achievements

We aim to take videos of faces and effectively estimate heart rates (HR) for real-world settings. We first built our own video dataset in a less controlled setup than the Mahnob-HCI dataset. Then we improved over our previous algorithm (ICCV2015). Our past algorithm was effective against illumination changes but less effective with complex motions of the face (e.g. pose changes, large translations). We developed an improved algorithm that uses triangulation to track face regions over pose changes more effectively. We have even tested on more challenging cases such as YouTube videos. We first uploaded self-made videos with complex motions to YouTube with known HRs and verified accurate HR estimation. We have also conducted tests on estimating emotions from our video-based cardiac algorithm.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

We have built our own dataset as indicated and we are improving our algorithm to robustly estimate heart rate (as we proposed). We have even found the new algorithm is effective on YouTube videos (with ground truth HR for validation). We are also doing a lot of investigations on its effectiveness in affective computing applications. These tests are being conducted on the dataset we built (where people watched different movie clips). We are also doing similar tests on real vlogger movie trailer reaction videos with promising results. The main drawback of our algorithm is that it is computationally expensive and therefore slow.

Strategy for Future Research Activity

We will work on improving the robustness of the algorithm and also its speed. We will also continue investigating emotion recognition using our algorithm, which is able to give the full cardiac pulse signal and not just the HR. By reading emotion from a physiological signal, we may be able to read into human emotional reactions at a deeper level than by just facial expressions alone.

Causes of Carryover

We plan to use the funds for travel, equipment, and collection of more data for next fiscal year. We expect that all funds will be used next fiscal year.

  • Research Products

    (5 results)

All 2018 2017

All Journal Article (5 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 2 results)

  • [Journal Article] Towards Taking Pulses Over YouTube to Determine Interest in Video Content2018

    • Author(s)
      Antony Lam, Kouyou Otsu, Keya Das, Yoshinori Kuno
    • Journal Title

      International Workshop on Frontiers of Computer Vision

      Volume: ー Pages: ー

    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] 映像解析に基づく頑健・高速な心拍数計測手法2018

    • Author(s)
      Kouyou Otsu, Keya Das, Hisato Fukuda, Antony Lam, Yoshinori Kobayashi, Yoshinori Kuno
    • Journal Title

      第24回画像センシングシンポジウム(SSII2018)予稿集

      Volume: ー Pages: ー

  • [Journal Article] 環境変化に頑健なビデオ映像による心拍数計測手法2017

    • Author(s)
      大津耕陽, 倉橋知己, Tilottoma Das, 福田悠人, Lam Antony, 小林貴訓, 久野義徳
    • Journal Title

      第23回画像センシングシンポジウム(SSII2017)予稿集

      Volume: IS2 Pages: 20

  • [Journal Article] Towards Detecting the Inner Emotions of Multiple People2017

    • Author(s)
      Keya Das, Kouyou Otsu, Antony Lam, Yoshinori Kobayashi, Yoshinori Kuno
    • Journal Title

      第99回パターン計測部会研究会

      Volume: ー Pages: ー

  • [Journal Article] Detecting Inner Emotions from Video Based Heart Rate Sensing2017

    • Author(s)
      Keya Das, Sarwar Ali, Kouyou Otsu, Hisato Fukuda, Antony Lam, Yoshinori Kobayashi, Yoshinori Kuno
    • Journal Title

      International Conference on Intelligent Computing

      Volume: 10363 Pages: 48~57

    • DOI

      https://doi.org/10.1007/978-3-319-63315-2_5

    • Peer Reviewed / Int'l Joint Research

URL: 

Published: 2018-12-17  

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