  In this research, Piano performances have been analyzed only based on visual
information. Computer vision algorithms, e.g., Hough transform and binary
thresholding, have been applied to find where the keyboard and specific keys
are located. At the same time, Convolutional Neural Networks(CNNs) has been
also utilized to find whether specific keys are pressed or not, and how much
intensity the keys are pressed only based on visual information. Especially for
detecting intensity, a new method of utilizing spatial, temporal CNNs model is
devised. Early fusion technique is especially applied in temporal CNNs
architecture to analyze hand movement. We also make a new dataset for training
each model. Especially when finding an intensity of a pressed key, both of
video frames and their optical flow images are used to train models to find
effectiveness.
