Authors:
Giacomo Boracchi
;
Vincenzo Caglioti
and
Alessandro Giusti
Affiliation:
Politecnico di Milano, Italy
Keyword(s):
Motion Blur, 3D Motion Reconstruction, Single Image Analysis, Blur Analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
We present an algorithm for analyzing a single calibrated image of a ball and for reconstructing its instantaneous motion (3D velocity and spin) by exploiting motion blur. We use several state-of-the-art image processing techniques for extracting information from the space-variant blurred image, then robustly integrate such information in a geometrical model of the 3D motion. We initially handle the simpler case in which the ball apparent translation is neglegible w.r.t. its spin, then extend the technique to handle the most general motion. We show extensive experimental results both on synthetic and camera images. In a broader scenario, we exploit this specific problem for discussing motivations, advantages and limits of reconstructing motion from motion blur.