SCA 18: Posters

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2632600

Browse

Browsing SCA 18: Posters by Issue Date

Filter results by year or month
Now showing 1 - 8 of 8
  • Thumbnail Image
    Item
    Frontmatter: ACM SIGGRAPH / Eurographics Symposium of Computer Animation 2018 - Posters
    (The Eurographics Association, 2018) ; Skouras, Melina
  • Thumbnail Image
    Item
    Untangling Layered Garments: An Implicit Approach
    (The Eurographics Association, 2018) Buffet, Thomas; Rohmer, Damien; Cani, Marie-Paule; Skouras, Melina
    The efficient animation of layers of garments is a challenging task, as it requires handling collisions and contacts between multiple thin surfaces, which may be difficult to untangle once inter-penetrations have occurred. We propose a novel geometric approach, based on implicit surfaces, to robustly handle such situations. At each animation step, our method converts the possibly intersecting garment surfaces to an implicit representation. They are then combined using a new binary operator that guarantees, as output, collision free states of the surfaces. In addition to a precise modeling of contact situations, our method enables to model the relative influence of each cloth layer, based on their relative stiffnesses and thicknesses.
  • Thumbnail Image
    Item
    Capturing Floor Exercise from Multiple Panning-Zooming Cameras
    (The Eurographics Association, 2018) Kobayashi, D.; Yamamoto, Masanobu; Skouras, Melina
    By panning and zooming camera, a system of the multiple cameras can obtain wider range of common field of views. It means that an image based motion capture system can measure bodies in motion of wider range. To do so, a key idea is a camera calibration by matching the panned and zoomed image with a panoramic image of the background. We show an experiment of motion capture of a gymnastic athlete in floor exercise by the calibrated cameras.
  • Thumbnail Image
    Item
    Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data
    (The Eurographics Association, 2018) Noshaba, Cheema; Hosseini, Somayeh; Sprenger, Janis; Herrmann, Erik; Du, Han; Fischer, Klaus; Slusallek, Philipp; Skouras, Melina
    Semantic segmentation of motion capture sequences plays a key part in many data-driven motion synthesis frameworks. It is a preprocessing step in which long recordings of motion capture sequences are partitioned into smaller segments. Afterwards, additional methods like statistical modeling can be applied to each group of structurally-similar segments to learn an abstract motion manifold. The segmentation task however often remains a manual task, which increases the effort and cost of generating large-scale motion databases. We therefore propose an automatic framework for semantic segmentation of motion capture data using a dilated temporal fully-convolutional network. Our model outperforms a state-of-the-art model in action segmentation, as well as three networks for sequence modeling. We further show our model is robust against high noisy training labels.
  • Thumbnail Image
    Item
    Latent Motion Manifold with Sequential Auto-Encoders
    (The Eurographics Association, 2018) Jang, Deok-Kyeong; Lee, Sung-Hee; Skouras, Melina
    We propose the sequential autoencoders for constructing latent motion manifold. Sequential autoencoders minimize the difference between the ground truth motion space distribution and reconstructed motion space distribution sampled from the latent motion manifold. Our method is based on sequence-to-sequence model for encoding the temporal information of human motion. We also adopt Wasserstein regularizer for matching encoded training distribution to the prior distribution of motion manifold. Our experiments show that randomly sampled points from trained motion manifold distribution become natural and valid motions.
  • Thumbnail Image
    Item
    VR Kino+Theatre: From the Ancient Greeks Into the Future of Media
    (The Eurographics Association, 2018) Velho, Luiz; Carvalho, Leonardo; Lucio, Djalma; Skouras, Melina
    VR Kino+Theatre is a media platform that combines theatrical performance with live cinema using virtual reality technology.
  • Thumbnail Image
    Item
    Local Models for Data Driven Inverse Kinematics of Soft Robots
    (The Eurographics Association, 2018) Holsten, Fredrik; Darkner, Sune; Engell-Nørregård, Morten P.; Erleben, Kenny; Skouras, Melina
    Soft robots are attractive because they have the potential of being safer, faster and cheaper than traditional rigid robots. If we can predict the shape of a soft robot for a given set of control parameters, then we can solve the inverse problem: to find an optimal set of control parameters for a given shape. This work takes a data-driven approach to create multiple local inverse models. This has two benefits: (1) We overcome the reality gap and (2) we gain performance and naive parallelism from using local models. Furthermore, we empirically prove that our approach outperforms a higher order global model.
  • Thumbnail Image
    Item
    Viewpoint Selection for Liquid Animations
    (The Eurographics Association, 2018) Suzuki, Chihiro; Kanai, Takashi; Skouras, Melina
    We propose a viewpoint selection method for time-varying liquid shapes in order to select the best viewpoint for liquid animations. First, viewpoint evaluation is performed by a combination of three evaluation terms; occlusion term, spatial feature term, and temporal feature term, and the viewpoint having the maximum evaluation value is selected as the “best viewpoint”. Through various experiments, it was confirmed that the results of this method is consistent with human intuition and that it can select viewpoints independent of the resolution of liquid meshes.