Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera

• URL: http://arxiv.org/abs/2106.08059v1
• Date: Tue, 15 Jun 2021 11:39:49 GMT
• Title: Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera
• Authors: Franziska Mueller, Micah Davis, Florian Bernard, Oleksandr Sotnychenko, Mickeal Verschoor, Miguel A. Otaduy, Dan Casas, Christian Theobalt
• Abstract summary: We present a novel method for real-time pose and shape reconstruction of two strongly interacting hands. Our approach combines an extensive list of favorable properties, namely it is marker-less. We show state-of-the-art results in scenes that exceed the complexity level demonstrated by previous work.
• Score: 79.41374930171469
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a novel method for real-time pose and shape reconstruction of two strongly interacting hands. Our approach is the first two-hand tracking solution that combines an extensive list of favorable properties, namely it is marker-less, uses a single consumer-level depth camera, runs in real time, handles inter- and intra-hand collisions, and automatically adjusts to the user's hand shape. In order to achieve this, we embed a recent parametric hand pose and shape model and a dense correspondence predictor based on a deep neural network into a suitable energy minimization framework. For training the correspondence prediction network, we synthesize a two-hand dataset based on physical simulations that includes both hand pose and shape annotations while at the same time avoiding inter-hand penetrations. To achieve real-time rates, we phrase the model fitting in terms of a nonlinear least-squares problem so that the energy can be optimized based on a highly efficient GPU-based Gauss-Newton optimizer. We show state-of-the-art results in scenes that exceed the complexity level demonstrated by previous work, including tight two-hand grasps, significant inter-hand occlusions, and gesture interaction.

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