Dynamic obstacle avoidance for real-time character animation

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possibl

Dynamic Obstacle Clearing for Real-time Character Animation

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possible

Data-driven constraint-based motion editing

The growth of motion capture systems has contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the various captured motions normally require specific needs. Consequently, modifying and reusing these motions in new situations – for example, retargeting it to a new environment – became an increasing area of research known as motion editing. In the last few years, human motion editing has become one of the most active research areas in the field of computer animation. In this thesis, we introduce and discuss a novel method for interactive human motion editing. Our main contribution is the development of a Low-dimensional Prioritized Inverse Kinematics (LPIK) technique that handles user constraints within a low-dimensional motion space – also known as the latent space. Its major feature is to operate in the latent space instead of the joint space. By construction, it is sufficient to constrain a single frame with LPIK to obtain a natural movement enforcing the intrinsic motion flow. The LPIK has the advantage of reducing the size of the Jacobian matrix as the motion latent space dimension is small for a coordinated movement compared to the joint space. Moreover, the method offers the compelling advantage that it is well suited for characters with large number of degrees of freedom (DoFs). This is one of the limitations of IK methods that perform optimizations in the joint space. In addition, our method still provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature. Essentially, our technique is based on the mathematical connections between linear motion models such as Principal Component Analysis (PCA) and Prioritized Inverse Kinematics (PIK). We use PCA as a first stage of preprocessing to reduce the dimensionality of the database to make it tractable and to encapsulate an underlying motion pattern. And after, to bound IK solutions within the space of natural-looking motions. We use PIK to allow the user to manipulate constraints with different priorities while interactively editing an animation. Essentially, the priority strategy ensures that a higher priority task is not affected by other tasks of lower priority. Furthermore, two strategies to impose motion continuity based on PCA are introduced. We show a number of experiments used to evaluate and validate (both qualitatively and quantitatively) the benefits of our method. Finally, we assess the quality of the edited animations against a goal-directed constraint-based technique, to verify the robustness of our method regarding performance, simplicity and realism