88 research outputs found
On the Two-View Geometry of Unsynchronized Cameras
We present new methods for simultaneously estimating camera geometry and time
shift from video sequences from multiple unsynchronized cameras. Algorithms for
simultaneous computation of a fundamental matrix or a homography with unknown
time shift between images are developed. Our methods use minimal correspondence
sets (eight for fundamental matrix and four and a half for homography) and
therefore are suitable for robust estimation using RANSAC. Furthermore, we
present an iterative algorithm that extends the applicability on sequences
which are significantly unsynchronized, finding the correct time shift up to
several seconds. We evaluated the methods on synthetic and wide range of real
world datasets and the results show a broad applicability to the problem of
camera synchronization.Comment: 12 pages, 9 figures, Computer Vision and Pattern Recognition (CVPR)
201
SmartMocap: Joint Estimation of Human and Camera Motion using Uncalibrated RGB Cameras
Markerless human motion capture (mocap) from multiple RGB cameras is a widely
studied problem. Existing methods either need calibrated cameras or calibrate
them relative to a static camera, which acts as the reference frame for the
mocap system. The calibration step has to be done a priori for every capture
session, which is a tedious process, and re-calibration is required whenever
cameras are intentionally or accidentally moved. In this paper, we propose a
mocap method which uses multiple static and moving extrinsically uncalibrated
RGB cameras. The key components of our method are as follows. First, since the
cameras and the subject can move freely, we select the ground plane as a common
reference to represent both the body and the camera motions unlike existing
methods which represent bodies in the camera coordinate. Second, we learn a
probability distribution of short human motion sequences (1sec) relative
to the ground plane and leverage it to disambiguate between the camera and
human motion. Third, we use this distribution as a motion prior in a novel
multi-stage optimization approach to fit the SMPL human body model and the
camera poses to the human body keypoints on the images. Finally, we show that
our method can work on a variety of datasets ranging from aerial cameras to
smartphones. It also gives more accurate results compared to the
state-of-the-art on the task of monocular human mocap with a static camera. Our
code is available for research purposes on
https://github.com/robot-perception-group/SmartMocap
The Potential of Using Exergame s for Correcting Posture Problems of Children
In Poland we observe a large scale of posture deformations and consequent health implications in
the population of school children. Therefore many pedagogical and medical societies are looking for
ways and methods of preventing and reversing this negative trend. The purpose of this article is to
present the potential of practical use of new posture correction interactive games among school
children. Some of the newest equipment and ways of detecting and registering natural human
movement have been presented. Teletransmision of data in real time makes it possible for a physiotherapist
to supervise and modify the player’s motor behavior. Creating visually attractive and
involving forms of physical exercise might help encourage and inspire children to reject a sedentary
lifestyle.3128930316Studia Edukacyjn
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