scholarly journals Manifold Learning Techniques for Editing Motion Capture Data

2021 ◽  
Author(s):  
◽  
Christopher Dean

<p>Streamlining the process of editing motion capture data and keyframe character animation is a fundamental problem in the animation field. This paper explores a new method for editing character animation, by using a data-driven pose distance as a falloff to interpolate new poses seamlessly into the sequence. This pose distance is the measure given by Green's function of the pose space Laplacian. The falloff shape and timing extent are naturally suited to the skeleton's range of motion, replacing the need for a manually customized falloff spline. This data-driven falloff is somewhat analogous to the difference between a generic spline and the ``magic wand'' selection in an image editor, but applied to the animation domain. It also supports powerful non-local edit propagation in which edits are applied to all similar poses in the entire animation sequence.</p>

2021 ◽  
Author(s):  
◽  
Christopher Dean

<p>Streamlining the process of editing motion capture data and keyframe character animation is a fundamental problem in the animation field. This paper explores a new method for editing character animation, by using a data-driven pose distance as a falloff to interpolate new poses seamlessly into the sequence. This pose distance is the measure given by Green's function of the pose space Laplacian. The falloff shape and timing extent are naturally suited to the skeleton's range of motion, replacing the need for a manually customized falloff spline. This data-driven falloff is somewhat analogous to the difference between a generic spline and the ``magic wand'' selection in an image editor, but applied to the animation domain. It also supports powerful non-local edit propagation in which edits are applied to all similar poses in the entire animation sequence.</p>


2020 ◽  
Vol 1 (2) ◽  
pp. 94-102
Author(s):  
Heri Priya Waspada ◽  
Ismanto Ismanto ◽  
Firman Hidayah

Abstrak Objektif. Proses pemodelan karakter 3D memegang peranan penting dalam menghasilkan model karakter 3D yang baik. Proses ini merupakan proses awal yang harus dilalui oleh seorang desainer dalam membuat sebuah model karakter 3D. Setelah proses pemodelan dikerjakan dengan baik agar karakter tersebut bisa dibuat bergerak maka diperlukan proses rigging. Dengan proses pemodelan dan rigging tersebut model karakter 3D bisa digunakan untuk menghasilkan animasi sesuai dengan keinginan animator. Tentunya seorang animator akan memerlukan kerja keras untuk membuat suatu adegan gerakan apabila animasi yang dibuat masih manual. Untuk itu dengan memanfaatkan data BVH, animator akan lebih ringan dalam membuat adegan animasinya. Hasil animasi karakter di tunjukkan kepada 40 responden untuk menilai dan menghasilkan rata-rata tingkat humanoid animasi karakter bernilai 65%. Material and Metode. Menganimasikan model karakter 3D memanfaatkan hasil motion capture (.bvh) Hasil. Animasi karakter 3D dengan menggunakan hasil motion capture menghasilkan animasi yang humanoid. Kesimpulan. Hasil motion capture merupakan susunan tulang yang sudah dilengkapi dengan hasil perekaman gerakan sehingga untuk memproduksi animasi model karakter 3D akan lebih mudah karena animator tidak perlu menggambar tiap gerakan yang diinginkan. Abstrack Objective. The process of modeling 3D characters plays an important role in producing good 3D character models. This process is the initial process that must be passed by a designer in creating a 3D character model. After the modeling process is done well so that the character can be moved, a rigging process is needed. With the modeling and rigging process, 3D character models can be used to produce animations in accordance with the wishes of the animator. Of course, an animator will need to work hard to create a motion scene if the animation created is still manual. For this reason, by utilizing BVH data, animators will be lighter in making their animated scenes. The results of the character animation were shown to 40 respondents to rate and produce an average humanoid character animation level of 65%.   Materials and Methods. Menganimasikan model karakter 3D memanfaatkan hasil motion capture (.bvh) Results. 3D character animation using the results of motion capture produces humanoid animation. Conclusion. The result of motion capture is the arrangement of bones that has been equipped with the results of recording the motion so that to produce animated 3D character models will be easier because the animator does not need to draw every desired movement.


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