Topic: Factors impacting video quality for sports analysis

I would like to use this thread to compile a list of quality-degrading factors in video, how much they are relevant to sport analysis, which component are involved, and how we may improve upon them.

This list should be general and relevant to anything that can provide a stream of image and store it on-device or transmit it to a computer (DSLR, Industrial camera, USB camera, IP camera, Smartphone, etc.). The trigger for this topic though, is the advent of high-quality, interchangeable, small lenses for surveillance-type cameras. We are now very near a day where little USB cameras can be considered serious imaging devices.

Please add your input, illustrative images, comments, remarks, additional degrading factors, formatting suggestions, etc.
Maybe at some point we can create a PDF or something. It should be useful for evaluating new hardware on the market and as a buyers guide.

Here are some topics that could be covered:

  • limited resolving power - lack of focus.

  • limited resolving power - long exposure.

  • limited resolving power - pixel count and lens resolution.

  • limited resolving power - image processing and JPEG compression.

  • spherical distortions - wide and ultra wide angle lenses.

  • vignetting - mechanical and optical.

  • noise.

  • flares.

  • limited temporal sampling granularity - low framerate.

  • temporal distortion - rolling shutter.

  • limited illuminance - low aperture.

  • limited dynamic range.

  • limited depth of field.

  • chromatic aberrations.

  • unfaithful color reproduction.

Re: Factors impacting video quality for sports analysis

Resolving power - lack of focus
- Impacts: the sharpness of details.
- Relevance to sport analysis: high.
- Component: Lens and lens mount.
- How to control or improve:
If the subject is always distant, a fixed focus camera may be sufficient. A camera with fixed focus should hopefully be focused at infinity in factory.
The most versatile solution is a manual focus that can be adjusted with a ring or lever.
The most efficient solution may be a motorized focus that we can control in software. (Logitech C920, Microsoft LifeCam). Note that even with motorized focus some webcams can't focus to infinity and anything farther than a few meters, will not be optimally focused.
Some lenses have variable focal length, in this case focusing sould usually be redone after changing the focal length.
Some devices have auto-focus capabilities, in this case care should be taken as to where in the image the focus has been locked.

Resolving power - long exposure
- Impacts: the sharpness of details on moving subjects.
- Relevance to sport analysis: very high.
- Component: Sensor.
- How to control or improve:
Some cameras have auto-exposure, they will adjust exposure to measured light levels. It lower reproducibility and the final exposure choosen may not be adequate (long exposure increases motion blur).
The most versatile solution is a camera for which exposure duration can be changed manually and is capable of short exposures (Exact requirement to be assessed).
- Compromise: low exposure means less light collected at the pixel sites. For laboratory setups artificial lights may be needed.

Resolving power - pixel count and lens resolution
- Impacts: the sharpness of details.
- Relevance to sport analysis: high.
- Component: Sensor and lens.
- How to control or improve:
Some devices are actually limited by their lens, when the lens itself is not able to project an image sharp enough to distinguish details that are two pixels apart.
More pixels is better but only if the lens is adequate. For a given sensor size, more pixels means smaller ones, which makes it more difficult for the lens to match resolution.
Lenses quality is measured in various metrics like lp/ph or MTF curves. A recent evolution is the use of Megapixel ratings. The lens fitted on the camera should have a megapixel rating at least as high as the pixel count of the sensor. (ex: A 3MP rated lens for 1920x1080 images). A good introductory resource on lens quality measurement methodology is at Cambridge in Colour.

Resolving power - image processing and JPEG compression
- Impacts: the sharpness of details.
- Relevance to sport analysis: high.
- Component: Image processing chip on the camera or recording software.
- How to control or improve:
The best solution is a camera that can provide the raw images to the computer, and to perform the color grading there.
The issue is that bandwidth is limited, so it is not always possible to transmit full color frames at the full framerate.
A camera should allow us to control the JPEG compression levels. (No USB camera currently does this to my knowledge).

Spherical distortions - wide angle and ultra wide angle lenses
- Impacts: measurements of distances and speeds.
- Relevance to sport analysis: mid to high.
- Component: Lens.
- How to control or improve:
Lenses with normal field of view (less than around 65°) usually have very low distortion.
For wide angle, a lens without distortions should be preferred, but the cost can skyrocket pretty quickly.
The distortion can be calibrated in software and taken into account for measurements.
- Compromise: A subject evolving at the same distance from the camera will cover less pixels, so less resolution.

3 (edited by Chas Tennis 2015-Jun-08 12:40:56)

Re: Factors impacting video quality for sports analysis

* Fast Shutter Speed for Small Motion Blur. (Estimated Motion Blur = V x T, where V is object velocity across the frame and T is the shutter speed.)

* 3D Multi-Camera Motion Capture Systems can measure in 3 dimensions, but at very high cost.  I believe that in some applications, 2 cameras might be applied to produce 3D measurements but with limitations under some circumstances.  For example, a golf swing might be a suitable subject for 3D measurements with 2 cameras where a tennis serve, more 3D, might not be because markers become obscured (require multicamera systems). I don't know the limitations, maybe 2 cameras would be feasible for many applications?     

* Cameras that produce orthogonal views are very useful for qualitative 3D analysis.  I'd always like to see the same tennis stroke in orthogonal XY plane and XZ planes, even if I could not measure it. 

UPDATE - NOTE THE SCANT INFORMATION I'VE SEEN ON THIS NEW CAMERA'S HIGH SPEED VIDEO IS NOT CLEAR -
The new Casio Ex 100Pro camera, reported to have manual shutter control, has a capability to operate 7 cameras from a WiFi trigger and have the high speed frames coordinated to within 1/2 millisecond.   That is according to preliminary information before its Jan 15th 2015 release in Japan.  I have been looking for Youtubes to evaluate the motion blur but have not seen any except the early Casio 100Pro Youtubes.

* I believe that multi-images -  in some form - can provide much better comparisons for rapid athletic motions than viewing in slow motion or stepping through single frames and trying to remember what you have seen. http://www.kinovea.org/en/forum/viewtopic.php?id=760

Re: Factors impacting video quality for sports analysis

Very good point about multiple view analysis. It departs a bit from what I thought with video quality-degrading issues, but I like to consider what the imaging system can deliver as a whole, be it a single or multiple camera system.

For 3D quantitative analysis, I think 2 cameras is the theoretical minimum but that real motion tracking applications never use less than 4 cameras. (I've used 2-camera systems for tracking eyes or fingers in a small volume, but as soon as you want to track body parts you move to 4 to 8 or even more).

So, what can constitute the main problems and defects of a multi-camera setup ? (Considering qualitative analysis only for now).
Mis-synchronization is probably one of the biggest… We can always synchronize to frame-level in software, but sub-frame sync requires hardware support. That's a clever use of WiFi for sure.
I don't know what constitute an acceptable synchronization level for sport analysis ? (I know that stereoscopy video requires almost pixel level sync for example).
On the subject, I have plans for a half software, half hardware sub-frame level synchronization method using the rolling shutter on consumer USB cameras and an Arduino powered strobe light, I'll post more details if I ever get it working.