Sporty software tells blurred balls’ directions

April 23rd, 2009 - 2:10 pm ICT by ANI  

London, Apr 23 (ANI): Commentators, who examine disputed line calls and coaches studying how well golfers and table-tennis players control balls, often face confusion when they see pictures and video stills of fast moving balls that appear as blurry streaks.

But, now a software, developed by scientists in Italy, could rid them of such confusion by determining a ball’s path and spin from a single blurry image.

Alessandro Giusti and his colleagues from the Polytechnic of Milan, who have developed a way to extract this data, has said that motion-blurred images contain far more information about a ball’s trajectory than frozen ones.

Usually a software just needs to look at the blurred streak of a moving ball in a photograph to easily detect the angle at which the ball is moving left or right and up or down in relation to the camera.The only hassle comes when it needs to work out how the ball is moving towards or away from the camera.

Since the ball will appear smaller when it is further away, just just measuring the changing width of the blur could solve the problem.

Existing software cannot do this because a motion-blurred image has transparent edges, confusing edge-detection algorithms.

But, the new algorithm developed by Giusti and his colleagues is based on the idea that a blurred image is equivalent to a series of sharp images added together.

They calculated what a series of brief exposures would look like and were able to work out a formula that describes the transparency of the blur towards its edges.

The new algorithm uses this formula to determine where a ball’s edge is and then to calculate the change in its distance from the camera.

Thus, by exploiting information such as the colour of the ball and its background, the software can compensate for variations in lighting, which may affect how transparent the ball appears.

Knowing the exposure time and the size of the ball, the team can work out the speed and direction of a ball from relatively short smears.

If the ball has some surface pattern, the software can even determine how it was spinning.

This capability could be a useful training aid for sports such as golf in which players use the spin of the ball to control its trajectory.

And it should also be cheaper than existing devices, because it uses only one stills camera while other systems need coordinated video cameras to follow a ball’s motion.

“This would be great. 3D is very expensive,” New Scientist quoted Chris Swanner of Sports Motion in California, which develops video training systems, as saying. (ANI)

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