A Knowledge-Based Approach to the Synthesis of Human Motion

Maiocchi, Roberto

doi:10.1007/978-4-431-68147-2_10

Cited by 10 publications

(11 citation statements)

References 30 publications

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“…A popular representation technique is to decompose motions into a sequence of states. These states could either be unique postures [12], [16] or loose clusters in posture space [7] spread over a duration of time. The Hidden Markov Model (HMM) [7], [23], [24] is a popular statistical framework where representative states and transition probabilities are learned from training sequences.…”

Section: Related Work 21 Motion Representationmentioning

confidence: 99%

“…State machines in procedural animation [8], [16], [17] have been formulated after manual analysis of common motions like walking, running, sitting, reaching, etc. The states are essentially kinematics-based, drawn from a collection of low-level DOF events, e.g., foot leaves ground, maximum torso inclination, etc.…”

Section: Related Work 21 Motion Representationmentioning

confidence: 99%

“…Last, knowledge-based analysis contributed by biomechanical and procedural animation research [12], [14], [16] has not been applied to motion representation. Templates codifying common motions (e.g., locomotion) have not been used in 3D data analysis even though they are widely used for synthesis.…”

Section: Introductionmentioning

confidence: 99%

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Semantic representation and correspondence for state-based motion transition

Ashraf

Wong

2003

IEEE Trans. Visual. Comput. Graphics

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Consistent transition algorithms preserve salient source motion features by establishing feature-based correspondence between motions and accordingly warping them before interpolation. These processes are commonly dubbed as preprocessing in motion transition literature. Current transition methods suffer from a lack of economical and generic preprocessing algorithms. Classical computer vision methods for human motion classification and correspondence are too computationally intensive for computer animation. This paper proposes an analytical framework that combines low-level kinematics analysis and high-level knowledge-based analysis to create states that provide coherent snapshots of body-parts active during the motion. These states are then corresponded via a globally optimal search tree algorithm. The framework proposed here is intuitive, controllable, and delivers results in near realtime. The validity and performance of the proposed system are tangibly proven with extensive experiments.

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Section: Related Work 21 Motion Representationmentioning

confidence: 99%

Section: Related Work 21 Motion Representationmentioning

confidence: 99%

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Semantic representation and correspondence for state-based motion transition

Ashraf

Wong

2003

IEEE Trans. Visual. Comput. Graphics

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“…where ¼´Ü Ýµ ´½ µ ½´Ü µ · ¾´Ü µ (9) ¼´Ü Ý Þµ ´½ µ´½ µ ½´Ü µ · ´½ µ ¾´Ü µ ·´½ µ ¿´Ü µ · ´Üµ (10) where ´Üµ from Eqn. 8…”

Section: Regularization Warp Of Participant Framespacesunclassified

“…Current cycle time Ì ¼´Ò µ Relative time in warped subspace starting at state n-1 Ì ¼´Ò µ Differential time in warped subspace starting at state n-1, from Eqns. (5) & (6) × £ Ò Time of state n after warp compensation × Ò Time of state n of framespace , i = 1,2,3,4´Üµ are the reference frames from participants , which are used for the linear weighted blending operation shown in Eqns (9). and(10).…”

mentioning

confidence: 99%

Generating Consistent Motion Transition via Decoupled Framespace Interpolation

Ashraf

Wong

2000

Computer Graphics Forum

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The framespace interpolation algorithm abstracts motion sequences as 1D signals, and interpolates between them to create higher dimension signals, with weights drawn from a user specified curve in a bounded region. We reformulate the algorithm to achieve motion‐state based transition via dynamic warping of framespaces and automatic transition timing via framespace frequency interpolation. Basis motions displaying diverse coordination configurations between upper and lower body‐halves, cannot be consistently corresponded at a macro level. We address this problem here, through decoupled blending of these halves to achieve true consistency, and eliminate accumulated phase differences via cosine phase warp functions. This generalization enables interpolation of motions with diverse coordinations between the upper and lower bodies.

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Six‐hundred indexed references on computer animation

Thalmann

1992

J. Visual. Comput. Animat.

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A Knowledge-Based Approach to the Synthesis of Human Motion

Cited by 10 publications

References 30 publications

Semantic representation and correspondence for state-based motion transition

Semantic representation and correspondence for state-based motion transition

Generating Consistent Motion Transition via Decoupled Framespace Interpolation

Six‐hundred indexed references on computer animation

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