Browsing by Author "Santos, Bruno M."
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- Deep convolutional neural networks applied to hand keypoints estimationPublication . Santos, Bruno M.; Pais, Pedro; Ribeiro, Francisco M.; Lima, José; Goncalves, Gil; Pinto, Vítor H.Accurate estimation of hand shape and position is an important task in various applications, such as human-computer interaction, human-robot interaction, and virtual and augmented reality. In this paper, it is proposed a method to estimate the hand keypoints from single and colored images utilizing the pre-trained deep convolutional neural networks VGG-16 and VGG-19. The method is evaluated on the FreiHAND dataset, and the performance of the two neural networks is compared. The best results were achieved by the VGG-19, with average estimation errors of 7.40 pixels and 11.36 millimeters for the best cases of two-dimensional and three-dimensional hand keypoints estimation, respectively.