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METHODS, SYSTEMS, AND COMPUTER READABLE MEDIA FOR ESTIMATION OF OPTICAL FLOW, DEPTH, AND EGOMOTION USING NEURAL NETWORK TRAINED USING EVENT-BASED LEARNING
METHODS, SYSTEMS, AND COMPUTER READABLE MEDIA FOR ESTIMATION OF OPTICAL FLOW, DEPTH, AND EGOMOTION USING NEURAL NETWORK TRAINED USING EVENT-BASED LEARNING
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机译:通过基于事件学习的神经网络训练来估计光学流量,深度和自我的方法,系统和计算机可读介质
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摘要
A method for prediction of an indication of motion using input from an event-based camera includes receiving events captured by an event-based camera, wherein each of the events represents a location of a change in pixel intensity, a polarity of the change, and a time. The method further includes discretizing the events into time discretized event volumes, each of which contain events that occur within a specified time range. The method further includes providing the time discretized event volumes as input to an encoder-decoder neural network trained to predict an indication of motion using a loss function that measures quality of image deblurring; generating, using the neural network, a prediction of the indication of motion. The method further includes using the prediction of the indication of motion in a machine vision application.
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