Paper Info
Title
Ball 3D Trajectory Reconstruction without Preliminary Temporal and Geometrical Camera Calibration
Abstract
This paper proposes a method for reconstructing 3D ball trajectories by using multiple temporally and geometrically uncalibrated cameras. To use cameras to measure the trajectory of a fast-moving object, such as a ball thrown by a pitcher, the cameras must be temporally synchronized and their position and orientation should be calibrated. In some cases, these conditions cannot be met, e.g., one cannot geometrically calibrate cameras when one cannot step into a baseball stadium. The basic idea of the proposed method is to use a ball captured by multiple cameras as a corresponding point. The method first detects a ball. Then, it estimates temporal difference between cameras. After that, the ball positions are used as corresponding points for geometrically calibrating the cameras. Experiments using actual pitching videos verify the effectiveness of our method.
Year
DOI
Venue
2017
10.1109/CVPRW.2017.26
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Keywords
Field
DocType
temporal difference estimation,ball capture,baseball stadium,camera orientation calibration,camera position calibration,temporally synchronized cameras,multiple geometrically uncalibrated cameras,multiple temporally uncalibrated cameras,ball 3D trajectory reconstruction
Computer vision,Temporal difference learning,Synchronization,Computer graphics (images),Computer science,Viewfinder,sports equipment,Camera resectioning,Artificial intelligence,Calibration,Trajectory,Three-CCD camera
Conference
Volume
Issue
ISSN
2017
1
2160-7508
ISBN
Citations 
PageRank 
978-1-5386-0734-3
0
0.34
References 
Authors
12
6
Name
Order
Citations
PageRank
Shogo Miyata121.54
Hideo Saito21147169.63
Kosuke Takahashi332.53
Dan Mikami411817.60
Mariko Isogawa565.86
Hideaki Kimata615029.40