Dataset for "A Novel Neural Network Architecture with Applications to 3D Animation and Interaction in Virtual Reality"

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gfnn_data.zip

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quadruped_data.zip

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framework_data.zip

data 13633 8 42456 document 13633 gfnn_code.zip application/zip 0ea6d83f5b2b19064ea9576383ff61c8 MD5 32472 2020-10-26 12:39:36 https://researchdata.bath.ac.uk/752/4/gfnn_code.zip 752 4 4 application/zip other Grid-functioned neural networks experiments code. en public cc_mit

gfnn_code.zip

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quadruped_code.zip

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framework_code.zip

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eira1_framework.pdf

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eira1_quadruped.pdf

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http://eprints.org/relation/isVersionOf https://researchdata.bath.ac.uk/id/document/13659 http://eprints.org/relation/isVolatileVersionOf https://researchdata.bath.ac.uk/id/document/13659 http://eprints.org/relation/isIndexCodesVersionOf https://researchdata.bath.ac.uk/id/document/13659 archive 6555 disk0/00/00/07/52 2020-11-20 13:44:19 2024-07-22 09:30:43 2020-11-20 13:44:19 data_collection show De La Dehesa Cueto-Felgueroso Javier J.Dehesa@bath.ac.uk 0000-0001-7692-2413 University of Bath TRUE Supervisor Padget Julian J.A.Padget@bath.ac.uk 0000-0003-1314-2094 University of Bath Supervisor Lutteroth Christof C.Lutteroth@bath.ac.uk 0000-0003-0634-7569 University of Bath Supervisor Vidler Andrew andrew.vidler@ninjatheory.com 0000-0001-6342-0844 Ninja Theory Dataset for "A Novel Neural Network Architecture with Applications to 3D Animation and Interaction in Virtual Reality" FB0010 FB0040 FB0090 dept_compsci machine learning, neural networks, animation, gesture recognition, virtual reality, human-computer interaction Synthetic evaluation data is stored in TfRecord format including the input and output values for each of the examples. Quadruped locomotion data is expressed in CSV, including the configuration of the character joints on each frame, and in TfRecord format, encoded as described in the thesis. Gesture recognition data is stored in CSV files where each row contains the position and orientation of both hands and the gesture being performed on each frame. Animation data is stored in CSV files where each row contains the position and orientation of each joint of the skeleton. User studies data is stored in JASP files encoding the answers of each participant to each question in the study. This is the dataset for the doctoral thesis "A Novel Neural Network Architecture with Applications to 3D Animation and Interaction in Virtual Reality" by Javier de la Dehesa Cueto-Felgueroso. See the original document for details. The dataset is structured in three parts. The files `gfnn_code.zip` and `gfnn_data.zip` contain the code and data for the experiments with grid-functioned neural networks discussed in chapter 3 of the thesis. The files `quadruped_code.zip` and `quadruped_data.zip` contain the code and data for the quadruped locomotion experiments and user study discussed in chapter 4. The files `framework_code.zip` and `framework_data.zip` contain the code and data for the human-character interaction framework experiments and user studies discussed in chapter 5. Each pair of files should be decompressed in the same directory, but separate from the other parts. Further details and instructions for each of the parts can be found within the corresponding compressed files. 2020-11-20 University of Bath public RightsHolder University of Bath Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/L016540/1 EPSRC Centre for Doctoral Training in Digital Entertainment cent_dig_ent Synthetic evaluation data has been generated programmatically. Quadruped locomotion data has been extracted from the dataset published as part of the article "Mode-Adaptive Neural Networks for Quadruped Motion Control" by Zhang et al. (2018). Gesture recognition data was collected with VR hardware in a custom-made virtual scenario, where the subject was presented with a signal indicating a gesture to perform, which they then did while pressing a button on the hand controller. Sword fighting animation data was motion captured with specialised equipment within the facilities of Ninja Theory, Ltd. User studies data was collected through online forms, filled after each condition of each of the studies. Quadruped locomotion data has been extracted from the dataset published as part of the article "Mode-Adaptive Neural Networks for Quadruped Motion Control" by Zhang et al. (2018). A selection of the original dataset was converted from the original BVH format into CSV and TensorFlow's TfRecord formats. Gesture recognition data was captured with an Oculus Rift kit. Animation data was captured with Vicon Bonita hardware. en 1 10.15125/BATH-00752 https://researchportal.bath.ac.uk/en/studentTheses/7615b2ba-0d3e-4081-a21f-de2329397945 thesis open