Performance capture of interacting characters with handheld kinects

76Citations
Citations of this article
60Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

We present an algorithm for marker-less performance capture of interacting humans using only three hand-held Kinect cameras. Our method reconstructs human skeletal poses, deforming surface geometry and camera poses for every time step of the depth video. Skeletal configurations and camera poses are found by solving a joint energy minimization problem which optimizes the alignment of RGBZ data from all cameras, as well as the alignment of human shape templates to the Kinect data. The energy function is based on a combination of geometric correspondence finding, implicit scene segmentation, and correspondence finding using image features. Only the combination of geometric and photometric correspondences and the integration of human pose and camera pose estimation enables reliable performance capture with only three sensors. As opposed to previous performance capture methods, our algorithm succeeds on general uncontrolled indoor scenes with potentially dynamic background, and it succeeds even if the cameras are moving. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Ye, G., Liu, Y., Hasler, N., Ji, X., Dai, Q., & Theobalt, C. (2012). Performance capture of interacting characters with handheld kinects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7573 LNCS, pp. 828–841). https://doi.org/10.1007/978-3-642-33709-3_59

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free