Frantic race for higher-quality images, at what cost?
Course effrénée aux images de meilleure qualité, à quel prix ?
Résumé
When implementing computer vision algorithms, the quality of the video input is a crucial parameter for systematic application as :
• Training and inference conditions of Deep Learning models may differ.
• Video quality may be downgraded due to sourcing or transfer encoding.
• Storage capacity may limit the volume/quantity of data available.
To better understand the sensitivity of inference with regarding video quality, we investigated the effect of video compression on the output of a human pose estimation network model.
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