Interactive motion deformation with prioritized constraints

Callennec, Benoît Le; Boulic, Ronan

doi:10.1145/1028523.1028545

Cited by 38 publications

(35 citation statements)

References 56 publications

(22 reference statements)

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“…Constraint-based techniques [9,8,10,11,12] provide a powerful framework to adapt recorded motions to different characters or to new situations from a set of user-specified constraints, such as end-effectors positions and end-effectors trajectories. To enforce a motion deformation an IK solver is normally used to solve user-specified constraints.…”

Section: Related Workmentioning

confidence: 99%

“…In particular, geometric constraints, such as the position of an end-effector in the three-dimensional space [20] or the trajectory of an end-effector [8], are more intuitive for interactive manipulation because the user can specify a goal just by dragging an end-effector to a new position. We equip animators with two types of constraints: key-frame and key-trajectory constraints as illustrated in Figure 1, both are firstly created in the joint space and then mapped into the latent space.…”

Section: Constraintsmentioning

confidence: 99%

“…The results are also compared against a constraint-based technique that performs deformations in the joint space [8]. After reviewing related work, we start describing the new approach for Data-Driven Constraint-Based Motion Editing.…”

Section: Introductionmentioning

confidence: 99%

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Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

Carvalho¹,

Boulic²,

Thalmann³

2009

Motion in Games

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Abstract. The growth of motion capture systems have 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 captured motions normally attend specific needs. As an effort for adapting and reusing captured human motions in new tasks and environments and improving the animator's work, we present and discuss a new data-driven constraintbased animation system for interactive human motion editing. This method offers the compelling advantage that it provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature.

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Section: Related Workmentioning

confidence: 99%

Section: Constraintsmentioning

confidence: 99%

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Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

Carvalho¹,

Boulic²,

Thalmann³

2009

Motion in Games

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“…Therefore, like many other blending methods, we add IK control on the feet to prevent sliding effects, by extending the prioritized IK described in [4,24] to the automatic generation of constraints in a dynamically evolving context [13]. This correction is efficient enough to not alter the real-time performance of the animation.…”

Section: Transition Between Locomotion and Jump (Without Obstacle)mentioning

confidence: 99%

Dynamic obstacle avoidance for real-time character animation

2006

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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.

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“…On the other hand, a common method is used to solve the inverse problem and constraints are used to enhance realism. These constraints come from movement studies [2] or are extracted from captured data [5].To enhance the realism of the synthesized movements, we propose a new constraint model based on the representation of joint synergies. Our constraint model integrates into the sensorimotor model proposed by Gibet et al [3].…”

mentioning

confidence: 99%

Modeling Joint Synergies to Synthesize Realistic Movements

Aubry

Julliard

Gibet

2010

Gesture in Embodied Communication and Human-Computer Interaction

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The need for making virtual humans more realistic keeps growing in domains like virtual reality, computer animation or interactive ergonomics. However, while many domains aim to enhance user's experience, applications in ergonomics mainly focus on the synthesis of realistic movements [1]. The number of works dealing with inverse kinematics to synthesize realistic movements highlights its difficulty. Among them, two categories can be sorted out of those works. On one hand, the whole inverse problem is learned from motion capture data and then reproduced [4]. On the other hand, a common method is used to solve the inverse problem and constraints are used to enhance realism. These constraints come from movement studies [2] or are extracted from captured data [5].To enhance the realism of the synthesized movements, we propose a new constraint model based on the representation of joint synergies. Our constraint model integrates into the sensorimotor model proposed by Gibet et al. [3]. This sensorimotor model, based on the Jacobian transpose method, includes a nonlinear gain function ("sigmoid" shape) to produce more natural pointing movements. We propose to replace this gain function by a new gain model learned from captured motions. After a description of our model, we present the learning process and the preliminary results that we obtained.We propose to model joint synergies as a vector of gains − → w , each w i being applied successively to the n degrees of freedom. This gain can be a function of time (t), current posture ( − → q t ), current angular speed (∆ − → q t ) and previous computed gain. It is computed at each step of the sensorimotor loop. The gain function may also use some constant parameters − → p to differentiate individuals.The size m of − → p is independant of the number n of degrees of freedom. These parameters may constitute the signature of an individual movements. We thus obtain the following model of joint synergies :The choice of the function f is discussed in the results but has no influence on the learning process of the parameters presented below. The goal is to find a value of − → p that makes possible the motion controller to reproduce recorded motions. We use a meta heuristic to adjust the parameters

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Interactive motion deformation with prioritized constraints

Abstract: In this paper, we present an interactive motion deformation method to modify animations so that they satisfy a set of prioritized constraints.

Cited by 38 publications

References 56 publications

Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

Dynamic obstacle avoidance for real-time character animation

Modeling Joint Synergies to Synthesize Realistic Movements

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