Data annotation involves labeling or tagging data to make it comprehensible and usable for Artificial Intelligence and machine learning algorithms.<\/p>\n
Skeletal Key Point was one of the features in the Video Annotation (VA) tool which allowed users to label human poses or anatomy of an object which can then be used to train the algorithms.\u00a0<\/span><\/p>\n One of our clients requested this feature as they received inaccurate data results that were sent to us. <\/span>Users were unable to annotate accurately with the existing Bounding Box tool, thus the data results were not detailed enough as it had some missing information about human poses.<\/span><\/p>\n Therefore, the main goal of the Skeletal Key Point project was to solve one of our existing client’s issues with their video annotation work. They wanted to use our platform and expertise to import data and annotate human poses with higher quality and accuracy<\/span>.<\/p>\n It achieved this by providing a visualisation of the functional connections between key points, which was one of the basic annotation tools in data labelling. <\/span>The connections made annotation errors very noticeable, and therefore less costly to fix. This capability was also supported in the review portal which allowed clients to review the annotated work, and it made the quality review and acceptance easier and less tedious.<\/span><\/p>\n There were 2 personas who used this feature:<\/span><\/p>\nProblem Statement<\/h4>\n
Goal<\/h4>\n
Users & Audience<\/h4>\n
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