University of Konstanz
Graduiertenkolleg / PhD Program
Computer and Information Science

Colloquium of the Department and the PhD Program

title

Using Large Motion-Capture-Databases for Analysis and Synthesis of Human Motions

speaker

Prof. Dr. Andreas Weber, University of Bonn
Bonn, Germany

date & place

Wednesday, 27.01.2010, 16:15 h
Room C 252

abstract

Data driven approaches to synthesize human motion is a common approach in computer graphics and animation. In this talk we will focus on two aspects that had obtained previously little attention but have shown to be extremely useful for synthesis and analysis of human motion data and applications such as motion capturing with few sensors.

  1. In many cases the data of motion capture data bases can be represented quite naturally using multi-linear representations using semantic information of the motions (such as performing actor, stylistic variants, ...)
  2. For semantically unclassified motions in large motion data bases we have shown recently that using certain medium dimensional (15-90 dimensional) feature sets for human motions the task of identifying locally similar regions becomes practical, if they are used for exact or approximate kd-tree-based nearest-neighbor searches. On the basis of kd-tree-based local neighborhood searches also a fast method for global similarity searches can be devised. We apply these methods to several tasks such as
    • "numerical and logical similarity searches"
    • reconstruction of motions from sparse marker sets, and
    • building so called "fat graphs",
    all tasks for which previously algorithms with preprocessing time quadratic in the size of the database and thus only applicable to small collections of motions had been presented.