Interactive pose and shape editing with simple sketches from different viewing angles.

The challenge of generating and creating humanoid 3D models is nowadays omnipresent in animation films, video games, and many other applications. To enhance and speed up this costly process, we propose an interactive method to infer 3D human poses and shapes from simple free-hand sketches. In contrast to previous work, our sketches are easy and fast to draw even for inexperienced users. Reconstructing the human 3D pose and shape from a single sketch is difficult due to the perspective projection resulting in ambiguous representations. We approach this challenge by adding a novel multi-view sketch interface for human pose estimation. Our simple sketch style allows for fast and intuitive, iterative refinement of not only the pose but also the shape using simple 2D interactions. The pose is inferred from a pre-trained neural network that is trained on a self-generated data set of sketches, derived by sampling 3D STAR models and rendering them in a sketch style. We conduct a user study to evaluate the accuracy, intuitiveness, and usability of our system in a real-world scenario. With our novel multi-view input system, we can effectively resolve ambiguities inherent to single sketch approaches while still delivering a fast and intuitive user experience. & COPY; 2023 Elsevier Ltd. All rights reserved.