Artwork

Indhold leveret af Kai Kunze. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kai Kunze eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !

Detecting an Offset-Adjusted Similarity Score based on Duchenne Smiles

8:49
 
Del
 

Manage episode 443660552 series 3605621
Indhold leveret af Kai Kunze. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kai Kunze eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Detecting interpersonal synchrony in the wild through ubiquitous wearable sensing invites promising new social insights as well as the possibility of new interactions between humans-humans and humans-agents. We present the Offset-Adjusted SImilarity Score (OASIS), a real-time method of detecting similarity which we show working on visual detection of Duchenne smile between a pair of users. We conduct a user study survey (N = 27) to measure a user-based interoperability score on smile similarity and compare the user score with OASIS as well as the rolling window Pearson correlation and the Dynamic Time Warping (DTW) method. Ultimately, our results indicate that our algorithm has intrinsic qualities comparable to the user score and measures well to the statistical correlation methods. It takes the temporal offset between the input signals into account with the added benefit of being an algorithm which can be adapted to run in real-time will less computational intensity than traditional time series correlation methods.

https://dl.acm.org/doi/10.1145/3544549.3585709

  continue reading

41 episoder

Artwork
iconDel
 
Manage episode 443660552 series 3605621
Indhold leveret af Kai Kunze. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kai Kunze eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Detecting interpersonal synchrony in the wild through ubiquitous wearable sensing invites promising new social insights as well as the possibility of new interactions between humans-humans and humans-agents. We present the Offset-Adjusted SImilarity Score (OASIS), a real-time method of detecting similarity which we show working on visual detection of Duchenne smile between a pair of users. We conduct a user study survey (N = 27) to measure a user-based interoperability score on smile similarity and compare the user score with OASIS as well as the rolling window Pearson correlation and the Dynamic Time Warping (DTW) method. Ultimately, our results indicate that our algorithm has intrinsic qualities comparable to the user score and measures well to the statistical correlation methods. It takes the temporal offset between the input signals into account with the added benefit of being an algorithm which can be adapted to run in real-time will less computational intensity than traditional time series correlation methods.

https://dl.acm.org/doi/10.1145/3544549.3585709

  continue reading

41 episoder

Alle episoder

×
 
Loading …

Velkommen til Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Hurtig referencevejledning

Lyt til dette show, mens du udforsker
Afspil