Building Hand Motion-Based Character Animation: The Case of Puppetry

Luo, Zhiqiang; Chen, I‐Ming; Yeo, Song Huat; Lin, Chih-Chung; Li, Tsai‐Yen

doi:10.1109/cw.2010.24

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…On the other hand, the study in [6] proposed Smart Glove to capture the hand motion to generate puppet animation, where the position of every joint (an actuator) is described by Denavit-Hartenberg (D-H) parameters with reference to the heel of the hand. Smart Glove captures hand motions with fifteen DOFs but cannot capture some motions of index, middle, ring, and little fingers.…”

Section: The Kinematic Model For Hand and Input Puppet Devicesmentioning

confidence: 99%

See 1 more Smart Citation

PuppetTalk: Conversation Between Glove Puppetry and Internet of Things

et al. 2021

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Section: The Kinematic Model For Hand and Input Puppet Devicesmentioning

confidence: 99%

“…Then the Laplace function of 3 ( ) is the convolution of ( 1 ) and ( ,2 ). From (6) we have 3 * ( ) = * ( ) * ( ) = λ * ( ) (s + λ)…”

Section: Pr[wrong Order] = Prmentioning

confidence: 99%

PuppetTalk: Conversation Between Glove Puppetry and Internet of Things

et al. 2021

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“…One well known technique is motion capturing: the performer's motions are mapped onto a virtual character. In most cases, a 1:1 mapping is used to achieve realistic Jacobson [12] Monkey [8] Eitsuka [7] Osawa [25] One-take Laszlo [18] Motion Doodles [33] Komura [15] Zhiqiang [21] Numaguchi [23] Kim [14] Krause [17] Mobile Animator [10] Shin [28] Creature…”

Section: Performance Animationmentioning

confidence: 99%

Creature Teacher

Fender

Müller

Lindlbauer

2015

Proceedings of the 3rd ACM Symposium on Spatial User Interaction

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Figure 1: With Creature Teacher users can quickly create organic movements by successively selecting and manipulating parts of a virtual creature. (a) The user is wearing an HMD and pinch gloves. (b) Body parts are selected using the left hand. (c) Selected parts are manipulated using the right hand. (d) Periodic movements are detected and played back repeatedly. ABSTRACTWe present Creature Teacher, a performance-based animation system for creating cyclic movements. Users directly manipulate body parts of a virtual character by using their hands. Creature Teacher's generic approach makes it possible to animate rigged 3D models with nearly arbitrary topology (e.g., non-humanoid) without requiring specialized user-to-character mappings or predefined movements. We use a bimanual interaction paradigm, allowing users to select parts of the model with one hand and manipulate them with the other hand. Cyclic movements of body parts during manipulation are detected and repeatedly played back -also while animating other body parts. Our approach of taking cyclic movements as an input makes mode switching between recording and playback obsolete and allows for fast and seamless creation of animations. We show that novice users with no animation background were able to create expressive cyclic animations for initially static virtual 3D creatures.

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“…However, such system lacks finer movements, like finger flexion, mapped in the movement of the animated character's hand. Animating a character's hand can require several artists illustrating the complicated hand movements, increasing the time and cost involved in the process [6], [7]. As already described for the healthcare industry, motion-capture gloves can help to avoid this cumbersome work and still provide an accurate solution.…”

Section: Introductionmentioning

confidence: 98%

Real-time hand tracking for rehabilitation and character animation

Moreira

Queirós

Fonseca

et al. 2014

2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH)

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Hand and finger tracking has a major importance in healthcare, for rehabilitation of hand function required due to a neurological disorder, and in virtual environment applications, like characters animation for on-line games or movies. Current solutions consist mostly of motion tracking gloves with embedded resistive bend sensors that most often suffer from signal drift, sensor saturation, sensor displacement and complex calibration procedures. More advanced solutions provide better tracking stability, but at the expense of a higher cost.The proposed solution aims to provide the required precision, stability and feasibility through the combination of eleven inertial measurements units (IMUs). Each unit captures the spatial orientation of the attached body. To fully capture the hand movement, each finger encompasses two units (at the proximal and distal phalanges), plus one unit at the back of the hand.The proposed glove was validated in two distinct steps: a) evaluation of the sensors' accuracy and stability over time; b) evaluation of the bending trajectories during usual finger flexion tasks based on the intra-class correlation coefficient (ICC).Results revealed that the glove was sensitive mainly to magnetic field distortions and sensors tuning. The inclusion of a hard and soft iron correction algorithm and accelerometer and gyro drift and temperature compensation methods provided increased stability and precision. Finger trajectories evaluation yielded high ICC values with an overall reliability within application's satisfying limits.The developed low cost system provides a straightforward calibration and usability, qualifying the device for hand and finger tracking in healthcare and animation industries.

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Building Hand Motion-Based Character Animation: The Case of Puppetry

Cited by 12 publications

References 8 publications

PuppetTalk: Conversation Between Glove Puppetry and Internet of Things

PuppetTalk: Conversation Between Glove Puppetry and Internet of Things

Creature Teacher

Real-time hand tracking for rehabilitation and character animation

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