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How To Tackle Video Annotation

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Advanced Training For CV Models

3 Key Aspects Of Video Annotation

 

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Annotating video data for computer vision initiatives can prove to be a difficult task. When it comes to video, the sheer size and complexity of video data present both technical and annotation challenges. To maximize this potential in video data, there are three key aspects of video annotation to consider when determining an annotation approach:

  1. Entity persistence
  2. Detecting state change
  3. Temporal tagging

An enterprise-grade labeling platform that employs a holistic video annotation approach can scale video annotation without diminishing complexity and compromising accuracy. With it your company can speed up time to value, build differentiation through computer vision, and mitigate the risk of poor performing models resulting from low-quality data.

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