Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation

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Abstract

This paper presents a multi-platform Web-based video annotator to support multimodal annotation that can be applied to several working areas, such as dance rehearsals, among others. The CultureMoves’ “Motion-Notes” Annotator was designed to assist the creative and exploratory processes of both professional and amateur users, working with a digital device for personal annotations. This prototype is being developed for any device capable of running in a modern Web browser. It is a real-time multimodal video annotator based on keyboard, touch and voice inputs. Five different ways of adding annotations have been already implemented: voice, draw, text, web URL, and mark annotations. Pose estimation functionality uses machine learning techniques to identify a person skeleton in the video frames, which gives the user another resource to identify possible annotations.

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Rodrigues, R., Madeira, R. N., Correia, N., Fernandes, C., & Ribeiro, S. (2019). Multimodal Web Based Video Annotator with Real-Time Human Pose Estimation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11872 LNCS, pp. 23–30). Springer. https://doi.org/10.1007/978-3-030-33617-2_3

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