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Hand Pose Estimation via Latent 2.5D Heatmap Regression
[chapter]
2018
Lecture Notes in Computer Science
Estimating the 3D pose of a hand is an essential part of human-computer interaction. Estimating 3D pose using depth or multiview sensors has become easier with recent advances in computer vision, however, regressing pose from a single RGB image is much less straightforward. The main difficulty arises from the fact that 3D pose requires some form of depth estimates, which are ambiguous given only an RGB image. In this paper we propose a new method for 3D hand pose estimation from a monocular
doi:10.1007/978-3-030-01252-6_8
fatcat:v3qp4leaire3ra2bywz7z5ab7y