CAnimAI

CAnimAI: Computer Animation and Artificial Intelligence

The workshop “CAnimAI: Computer Animation and Artificial Intelligence” aims to bring together academic researchers and practitioners (developers, designers, engineers and artists) to cooperate and exchange around computer animation and more generally digital arts and artificial intelligence. The workshop is interdisciplinary and it particularly seeks for works involving artificial intelligence techniques applied to computer animation and digital media management and engineering. The workshop will be held as a joint event with IEA/AIE 2017 conference in Arras.

Authors are invited to submit original works in full papers (6 pages) or extended abstracts for preliminary or ongoing works and demonstrations (2 pages). The authors should submit their paper via EasyChair. Submissions should follow Springer-Verlag formatting instructions available here.

Topics of interest are (but not limited to):

  • Digital arts
  • Computer animation
  • 2D and 3D modeling
  • Motion capture and modeling
  • Computer generated animation and visual effects
  • Computer vision and computer graphics
  • Image & video Analysis
  • Pattern recognition and classification
  • Motion analysis and object tracking
  • Object, event, expression and scene recognition
  • Video annotation and content analysis
  • Augmented/Virtual Reality
  • Artificial intelligence and Al-based animation, computer vision
  • Computer and mobile technologies for computer graphics and animation
  • Applications and prototypes for dances, puppetry theatre and other performance arts
  • Applications and prototypes for teaching and disseminating performance arts
  • Digital media and systems for preserving cultural heritage and performance arts
  • AI-based digital media management systems (indexing, querying, summarizing…)

Important dates

  • Submissions due: April 30th, 2017
  • Notification of acceptance: May 15th, 2017
  • Camera ready copies due: May 30th, 2017
  • Workshop date: June 27th, 2017

Committees

Co-chairs

  • Mohd Shafry Bin Mohd Rahim (MA)
  • Nguyen Huu Hoa (VN)
  • Sylvain Lagrue (FR)
  • Pradorn Sureephong (TH)
  • Karim Tabia (FR)
  • Bui The Duy (VN)
  • Hongchuan Yu (UK)
  • Jian J Zhang (UK)

Local chairs

  • Sylvain Lagrue (Univ. Artois, FR)
  • Karim Tabia (Univ. Artois, FR)

PC members

  • Mohd Shafry Bin Mohd Rahim (MA)
  • Nathalie Chetcuti-Sperandio (FR)
  • Nguyen Huu Hoa (VN)
  • Sylvain Lagrue (Univ. Artois, FR)
  • Pham Nguyen Khang (VN)
  • Do Thanh Nghi (VN)
  • Pradorn Sureephong (TH)
  • Karim Tabia (Univ. Artois, FR)
  • Bui The Duy (VN)
  • Serjan Vesic (CNRS, FR)
  • Hongchuan Yu (UK)
  • Jian J Zhang (UK)

This workshop receives support from AniAge (High Dimensional Heterogeneous Data based Animation Techniques for Southeast Asian Intangible Cultural Heritage Digital Content) project “Marie Skłodowska-Curie Actions RISE (Research and Innovation Staff Exchange)”, H2020-MSCA-RISE-2015.

Program

1:30pm Welcome
1:35pm Clarisse BardiotDocumenting Performing Arts with Digital Technologies (Invited talk)
2:10pm Ma Thi ChauA Labanotation based ontology for representing Vietnamese folk dances
2:30pm Nguyen Thi NganTechnologies for the culture propagation from tradition to contemporary life in museum
2:50pm Le Thanh HaThe project: Multimedia application tools for Vietnamese intangible cultural heritage conservation
3:10pm Mohd Azmie Bin Tajor AmirudinAutomatic Annotation of Traditional Dance Data Using Motion Features
3:30pmCoffee break
4:00pm Anuar NurwinaZapin dance
4:25pm Pradorn SureephongTraditional Thai Dance Knowledge Archiving and Visualization Using Dance Notation Method
4:50pm Hongchuan YuMotion Analysis and Data Mining
5:15pm Yipeng QinFast and Exact Geodesic Computation using Edge-based Windows Grouping
5:35pm Pradorn SureephongDance Training Tool using Kinect-based Skeleton Tracking and Evaluating Dancer’s Performance
5:55pm Paweena SuebsombutImplementing A Tool for Translating Dance Notation to Display in 3D Animation: A Case Study of Traditional Thai
6:15pmEnd