This paper describes algorithms for the animation of men and women performing three dynamic athletic behaviors: running, bicycling, and vaulting. We animate these behaviors using control algorithms that cause a physically realistic model to perform the desired maneuver. For example, control algorithms allow the simulated humans to maintain balance while moving their arms, to run or bicycle at a variety of speeds, and to perform a handspring vault. Algorithms for group behaviors allow a number of simulated bicyclists to ride as a group while avoiding simple patterns of obstacles. We add secondarymotion to the animations with springmass simulations of clothing driven by the rigid-body motion of the simulated human. For each simulation, we compare the computed motion to that of humans performing similar maneuvers both qualitatively through the comparison of real and simulated video images and quantitatively through the comparison of simulated and biomechanical data.

Real-time control of three-dimensional avatars is an important problem in the context of computer games and virtual environments. Avatar animation and control is difficult, however, because a large repertoire of avatar behaviors must be made available, and the user must be able to select from this set of behaviors, possibly with a low-dimensional input device. One appealing approach to obtaining a rich set of avatar behaviors is to collect an extended, unlabeled sequence of motion data appropriate to the application. In this paper, we show that such a motion database can be preprocessed for flexibility in behavior and efficient search and exploited for real-time avatar control. Flexibility is created by identifying plausible transitions between motion segments, and efficient search through the resulting graph structure is obtained through clustering. Three interface techniques are demonstrated for controlling avatar motion using this data structure: the user selects from a set of available choices, sketches a path through an environment, or acts out a desired motion in front of a video camera. We demonstrate the flexibility of the approach through four different applications and compare the avatar motion to directly recorded human motion.

There have been several recent efforts to build behavior-based autonomous creatures. While competent autonomous action is highly desirable, there is an important need to integrate autonomy with "directability". In this paper we discuss the problem of building autonomous animated creatures for interactive virtual environments which are also capable of being directed at multiple levels. We present an approach to control which allows an external entity to "direct" an autonomous creature at the motivational level, the task level, and the direct motor level. We also detail a layered architecture and a general behavioral model for perception and action-selection which incorporates explicit support for multi-level direction. These ideas have been implemented and used to develop several autonomous animated creatures. 1. INTRODUCTION Since Reynold's seminal paper in 1987, there have been a number of impressive papers on the use of behavioral models to generate computer animation. The motivati...

We apply manipulation planning to computer animation. A new path planner is presented that automatically computes the collision-free trajectories for several cooperating arms to manipulate a movable object between two configurations. This implemented planner is capable of dealing with complicated tasks where regrasping is involved. In addition, we present a new inverse kinematics algorithm for the human arms. This algorithm is utilized by the planner for the generation of realistic human arm motions as they manipulate objects. We view our system as a tool for facilitating the production of animation.

This article describes a process that greatly expands the range of possible motions. Mixing motions selected from a database lets you create a newmotion to exact specifications. The synthesized motion retains the original motions' subtle qualities, such as the realism of motion capture or the expressive, exaggerated qualities of artistic animation. Ourmethod provides a newway to achieve inverse kinematics capability---for example, placing the hands or feet of an articulated figure in specific positions. It proves useful for both real-time graphics and prerendered animation production.

This paper describes an algorithm for automatically adapting existing simulated behaviors to new characters. Animating a new character is difficult because a control system tuned for one character will not, in general, work on a character with different limb lengths, masses, or moments of inertia. The algorithm presented here adapts the control system to a new character in two stages. First, the control system parameters are scaled based on the sizes, masses, and moments of inertia of the new and the original characters. Then a subset of the parameters is fine-tuned using a search process based on simulated annealing. To demonstrate the effectiveness of this approach, we animate the running motion of a woman, child, and imaginary character by modifying the control system for a man. We also animate the bicycling motion of a second imaginary character by modifying the control system for a man. We evaluate the results of this approach by comparing the motion of the simulated human runners...

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The overall movement of articulated bodies (such as the human body) is enabled by the coordinated movement of its rigid body parts. The body parts are connected by joints and, in general, move differently. For interpreting these movements as the movement of one single body, it seems to be necessary to incorporate knowledge in the analysis process. Therefore, in order to recognize pedestrians from monocular image sequences, we introduce a model-based approach. We represent the human body by a volume model and use medical motion data for simulating the movement of walking. This knowledge is exploited to determine the 3D-position as well as the posture of an observed person. By applying a Kalman filter we incrementally estimate the model parameters in consecutive images. Our approach has been tested on real image data.

Even such simple tasks as placing a box on a shelf are difficult to animate, because the animator must carefully position the character to satisfy geometric and balance constraints while creating motion to perform the task with a natural-looking style. In this paper, we explore an approach for animating characters manipulating objects that combines the power of path planning with the domain knowledge inherent in data-driven, constraint-based inverse kinematics. A path planner is used to find a motion for the object such that the corresponding poses of the character satisfy geometric, kinematic, and posture constraints. The inverse kinematics computation of the character’s pose resolves redundancy by biasing the solution toward natural-looking poses extracted from a database of captured motions. Having this database greatly helps to increase the quality of the output motion. The computed path is converted to a motion trajectory using a model of the velocity profile. We demonstrate the effectiveness of the algorithm by generating animations across a wide range of scenarios that cover variations in the geometric, kinematic, and dynamic models of the character, the manipulated object, and obstacles in the scene.

When sufficient computing power is available, dynamic simulation can be used as a source of motion for real-time, interactive virtual environments. In this paper, we explore techniques for reducing the computational cost of simulating groups of creatures by using less accurate simulations for individuals when they are less important to the viewer or to the action in the virtual world. The less accurate, or lower level of detail, simulations can be dynamic with fewer degrees of freedom, hybrid kinematic /dynamic, or purely kinematic. As a test of the effectiveness of this approach, we implemented an environment with dynamically simulated legged creatures. Because the creatures switch smoothly among different levels of detail for the underlying simulation, we can achieve real-time performance for a larger group of creatures than would be possible if each creature were dynamically simulated. To be useful in this test case, the method must meet two criteria: the outcome of the game must be...