Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Outdoor human motion capture by simultaneous optimization of pose and camera parameters
AU - Elhayek, Ahmed
AU - Stoll, Carsten
AU - Kim, Kwang In
AU - Theobalt, Christian
PY - 2015/9
Y1 - 2015/9
N2 - We present a method for capturing the skeletal motions of humans using a sparse set of potentially moving cameras in an uncontrolled environment. Our approach is able to track multiple people even in front of cluttered and non-static backgrounds, and unsynchronized cameras with varying image quality and frame rate. We completely rely on optical information and do not make use of additional sensor information (e.g. depth images or inertial sensors). Our algorithm simultaneously reconstructs the skeletal pose parameters of multiple performers and the motion of each camera. This is facilitated by a new energy functional that captures the alignment of the model and the camera positions with the input videos in an analytic way. The approach can be adopted in many practical applications to replace the complex and expensive motion capture studios with few consumer-grade cameras even in uncontrolled outdoor scenes. We demonstrate this based on challenging multi-view video sequences that arecaptured with unsynchronized and moving (e.g. mobile-phone or GoPro) cameras.
AB - We present a method for capturing the skeletal motions of humans using a sparse set of potentially moving cameras in an uncontrolled environment. Our approach is able to track multiple people even in front of cluttered and non-static backgrounds, and unsynchronized cameras with varying image quality and frame rate. We completely rely on optical information and do not make use of additional sensor information (e.g. depth images or inertial sensors). Our algorithm simultaneously reconstructs the skeletal pose parameters of multiple performers and the motion of each camera. This is facilitated by a new energy functional that captures the alignment of the model and the camera positions with the input videos in an analytic way. The approach can be adopted in many practical applications to replace the complex and expensive motion capture studios with few consumer-grade cameras even in uncontrolled outdoor scenes. We demonstrate this based on challenging multi-view video sequences that arecaptured with unsynchronized and moving (e.g. mobile-phone or GoPro) cameras.
KW - markerless human motion capture
KW - outdoor capture
KW - moving cameras
KW - I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Animation
U2 - 10.1111/cgf.12519
DO - 10.1111/cgf.12519
M3 - Journal article
VL - 34
SP - 86
EP - 98
JO - Computer Graphics Forum
JF - Computer Graphics Forum
SN - 0167-7055
IS - 6
ER -