Action Recognition Utilizing YGAR Dataset

• URL: http://arxiv.org/abs/2310.00831v1
• Date: Mon, 2 Oct 2023 00:43:45 GMT
• Title: Action Recognition Utilizing YGAR Dataset
• Authors: Shuo Wang, Amiya Ranjan and Lawrence Jiang
• Abstract summary: The scarcity of high quality actions video data is a bottleneck in the research and application of action recognition. We present a new 3D actions data simulation engine and generate 3 sets of sample data to demonstrate its current functionalities.
• Score: 5.922172844641853
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The scarcity of high quality actions video data is a bottleneck in the research and application of action recognition. Although significant effort has been made in this area, there still exist gaps in the range of available data types a more flexible and comprehensive data set could help bridge. In this paper, we present a new 3D actions data simulation engine and generate 3 sets of sample data to demonstrate its current functionalities. With the new data generation process, we demonstrate its applications to image classifications, action recognitions and potential to evolve into a system that would allow the exploration of much more complex action recognition tasks. In order to show off these capabilities, we also train and test a list of commonly used models for image recognition to demonstrate the potential applications and capabilities of the data sets and their generation process.

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