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thearn
webcam-pulse-detector
Python2013–2019
thearn / webcam-pulse-detector

webcam-pulse-detector

A python application that detects and highlights the heart-rate of an individual (using only their own webcam) in real-time.

6Distinct people
8Mentions
0Explicit recommenders
3.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A python application that detects and highlights the heart-rate of an individual (using only their own webcam) in real-time.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2013-04-16 03:21:05 UTC to 2019-06-13 08:42:31 UTC.

01232013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC312
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC000
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101

What Hacker News says

8 sources
I use OpenCV for reading and writing real-time video streams (like webcams or video frames) for my hobby computer vision projects, but tend to use other ML or image-specific libraries for actual processing. The cascade classifiers in OpenCV are okay, but it isn't too difficult to set up something comparable in scikit-learn that is more modern and robust. Though a bit less performant if you do need real-time response though. Best example that I have is a pulse rate detector that I put together, that uses OpenCV for video frame extraction & display but bare numpy/scipy for the rest. https://github.com/thearn/webcam-pulse-detector
In Ask HN: What are the best resources to learn computer vision?
For this purpose, MIT's Eulerian Video Magnification is next to impossible when you have both color changes and large motions (it is better suited to magnifying small motions, or subtle color changes in unmoving patches). NASA Glenn's thearn has developed another approach which has the same problems (https://github.com/thearn/webcam-pulse-detector). We developed our own solution, involving (among other things) pixel-accurate facial feature detection and filtering methods not subject to FFT's regularity assumption
In Show HN: See what makes presidential candidates' hearts beat faster (Live)

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