Posing 3D Models from Drawing

Inferring the 3D pose of a character from a drawing is a complex and under-constrained problem. Solving it may help automate various parts of an animation production pipeline such as pre-visualisation. In this paper, a novel way of inferring the 3D pose from a monocular 2D sketch is proposed. The proposed method does not make any external assumptions about the model, allowing it to be used on different types of characters. The inference of the 3D pose is formulated as an optimisation problem and a parallel variation of the Particle Swarm Optimisation algorithm called PARAC-LOAPSO is utilised for searching the minimum. Testing in isolation as well as part of a larger scene, the presented method is evaluated by posing a lamp, a horse and a human character. The results show that this method is robust, highly scalable and is able to be extended to various types of models

Human motion retrieval based on freehand sketch

In this paper, we present an integrated framework of human motion retrieval based on freehand sketch. With some simple rules, the user can acquire a desired motion by sketching several key postures. To retrieve efficiently and accurately by sketch, the 3D postures are projected onto several 2D planes. The limb direction feature is proposed to represent the input sketch and the projected-postures. Furthermore, a novel index structure based on k-d tree is constructed to index the motions in the database, which speeds up the retrieval process. With our posture-by-posture retrieval algorithm, a continuous motion can be got directly or generated by using a pre-computed graph structure. What's more, our system provides an intuitive user interface. The experimental results demonstrate the effectiveness of our method. © 2014 John Wiley & Sons, Ltd

The Line of Action: an Intuitive Interface for Expressive Character Posing

International audienceThe line of action is a conceptual tool often used by cartoonists and illustrators to help make their figures more consistent and more dramatic. We often see the expression of characters--may it be the dynamism of a super hero, or the elegance of a fashion model--well captured and amplified by a single aesthetic line. Usually this line is laid down in early stages of the drawing and used to describe the body's principal shape. By focusing on this simple abstraction, the person drawing can quickly adjust and refine the overall pose of his or her character from a given viewpoint. In this paper, we propose a mathematical definition of the line of action (LOA), which allows us to automatically align a 3D virtual character to a user specified LOA by solving an optimization problem. We generalize this framework to other types of lines found in the drawing literature, such as secondary lines used to place arms. Finally, we show a wide range of poses and animations that were rapidly created using our system

Sketch2Pose : estimating a 3D character pose from a bitmap sketch

Artists frequently capture character poses via raster sketches, then use these drawings as a reference while posing a 3D character in a specialized 3D software --- a time-consuming process, requiring specialized 3D training and mental effort. We tackle this challenge by proposing the first system for automatically inferring a 3D character pose from a single bitmap sketch, producing poses consistent with viewer expectations. Algorithmically interpreting bitmap sketches is challenging, as they contain significantly distorted proportions and foreshortening. We address this by predicting three key elements of a drawing, necessary to disambiguate the drawn poses: 2D bone tangents, self-contacts, and bone foreshortening. These elements are then leveraged in an optimization inferring the 3D character pose consistent with the artist's intent. Our optimization balances cues derived from artistic literature and perception research to compensate for distorted character proportions. We demonstrate a gallery of results on sketches of numerous styles. We validate our method via numerical evaluations, user studies, and comparisons to manually posed characters and previous work

Adding dynamics to sketch-based character animations

International audienceCartoonists and animators often use lines of action to emphasize dynamics in character poses. In this paper, we propose a physically-based model to simulate the line of action's motion, leading to rich motion from simple drawings. Our proposed method is decomposed into three steps. Based on user-provided strokes, we forward simulate 2D elastic motion. To ensure continuity across keyframes, we re-target the forward simulations to the drawn strokes. Finally, we synthesize a 3D character motion matching the dynamic line. The fact that the line can move freely like an elastic band raises new questions about its relationship to the body over time. The line may move faster and leave body parts behind, or the line may slide slowly towards other body parts for support. We conjecture that the artist seeks to maximize the filling of the line (with the character's body)---while respecting basic realism constraints such as balance. Based on these insights, we provide a method that synthesizes 3D character motion, given discontinuously constrained body parts that are specified by the user at key moments

Repurpose 2D Animations for a VR Environment using BDH Shape Interpolation

Virtual Reality technology has spread rapidly in recent years. However, its growth risks ending soon due to the absence of quality content, except for few exceptions. We present an original framework that allows artists to use 2D characters and animations in a 3D Virtual Reality environment, in order to give an easier access to the production of content for the platform. In traditional platforms, 2D animation represents a more economic and immediate alternative to 3D. The challenge in adapting 2D characters to a 3D environment is to interpret the missing depth information. A 2D character is actually flat, so there is not any depth information, and every body part is at the same level of the others. We exploit mesh interpolation, billboarding and parallax scrolling to simulate the depth between each body segment of the character. We have developed a prototype of the system, and extensive tests with a 2D animation production show the effectiveness of our framework

Repurpose 2D Character Animations for a VR Environment Using BDH Shape Interpolation.

Virtual Reality technology has spread rapidly in recent years. However, its growth risks ending soon due to the absence of quality content, except for few exceptions. We present an original framework that allows artists to use 2D characters and animations in a 3D Virtual Reality environment, in order to give an easier access to the production of content for the platform. In traditional platforms, 2D animation represents a more economic and immediate alternative to 3D. The challenge in adapting 2D characters to a 3D environment is to interpret the missing depth information. A 2D character is actually flat, so there is not any depth information, and every body part is at the same level of the others. We exploit mesh interpolation, billboarding and parallax scrolling to simulate the depth between each body segment of the character. We have developed a prototype of the system, and extensive tests with a 2D animation production show the effectiveness of our framework

Interactive Sketching of Mannequin Poses

It can be easy and even fun to sketch humans in different poses. In contrast, creating those same poses on a 3D graphics 'mannequin' is comparatively tedious. Yet 3D body poses are necessary for various downstream applications. We seek to preserve the convenience of 2D sketching while giving users of different skill levels the flexibility to accurately and more quickly pose/refine a 3D mannequin. At the core of the interactive system, we propose a machine-learning model for inferring the 3D pose of a CG mannequin from sketches of humans drawn in a cylinder-person style. Training such a model is challenging because of artist variability, a lack of sketch training data with corresponding ground truth 3D poses, and the high dimensionality of human pose-space. Our unique approach to synthesizing vector graphics training data underpins our integrated ML-and-kinematics system. We validate the system by tightly coupling it with a user interface, and by performing a user study, in addition to quantitative comparisons