Autonomous real-time model building for optical motion capture

被引：0

作者：

Rajko, S ^{[1
]}

Qian, G ^{[1
]}

机构：

[1] Arizona State Univ, Arts Media & Engn Program, Tempe, AZ 85287 USA

来源：

2005 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), VOLS 1-5 | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a robust framework for real-time processing of 3D motion capture data. It autonomously analyzes the input data to build a model of the observed subjects, and is expected to perform in situations where the observed features are unstable or frequently occluded. We have implemented the method and presently rely on a marker based motion capture system to provide unlabeled 3D coordinates of non-occluded markers. However, we hope this to be a step towards using regular video camera systems with feature detection to perform autonomous markerless motion capture.

引用

页码：3397 / 3400

页数：4

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