DEEP-LEARNING MOTION PRIORS FOR FULL-BODY PERFORMANCE CAPTURE IN REAL-TIME
First Claim
1. A method for motion capture, the method being implemented by a processor configured to execute machine-readable instructions, the method comprising:
- obtaining a deep learning model;
obtaining training data and training the deep learning model using the training data, the training data including temporal and spatial information regarding one or more actors'"'"' motion captured previously;
receiving, from one or more motion capture sensors, real-time motion data for an actor'"'"'s movement; and
estimating motion information regarding the actor'"'"'s motion based on the received motion data using the deep learning model.
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Accused Products
Abstract
Training data from multiple types of sensors and captured in previous capture sessions can be fused within a physics-based tracking framework to train motion priors using different deep learning techniques, such as convolutional neural networks (CNN) and Recurrent Temporal Restricted Boltzmann Machines (RTRBMs). In embodiments employing one or more CNNs, two streams of filters can be used. In those embodiments, one stream of the filters can be used to learn the temporal information and the other stream of the filters can be used to learn spatial information. In embodiments employing one or more RTRBMs, all visible nodes of the RTRBMs can be clamped with values obtained from the training data or data synthesized from the training data. In cases where sensor data is unavailable, the input nodes may be unclamped and the one or more RTRBMs can generate the missing sensor data.
25 Citations
18 Claims
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1. A method for motion capture, the method being implemented by a processor configured to execute machine-readable instructions, the method comprising:
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obtaining a deep learning model; obtaining training data and training the deep learning model using the training data, the training data including temporal and spatial information regarding one or more actors'"'"' motion captured previously; receiving, from one or more motion capture sensors, real-time motion data for an actor'"'"'s movement; and estimating motion information regarding the actor'"'"'s motion based on the received motion data using the deep learning model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for motion capture, the system comprising one or more of a processor configured to execute machine-readable instructions such that when the machine-readable instructions are executed, the process is caused to perform:
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obtaining a deep learning model; obtaining training data and training the deep learning model using the training data, the training data including temporal and spatial information regarding one or more actors'"'"' motion captured previously; receiving, from one or more motion capture sensors, real-time motion data for an actor'"'"'s movement; and estimating motion information regarding the actor'"'"'s motion based on the received motion data using the deep learning model. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification