As a precursor, you need to know the speed of objects, most typically people.

 

Speed of People

 

The faster a person moves, the more likely you are to miss an action. You know the 'speed' of frame rate - 1 frame per second, 10 frames per second, 30, etc., but how many frames do you need for reliable capture?

 

Here's how fast people move.

 

For a person walking, a leisurely, ordinary pace is ~4 feet per second, covering this 20 foot wide FoV in ~5 seconds:

 

Note: Click here to watch the demo on IPVM

For a person running, our subject goes through the 20' FOV in ~1.25 seconds, meaning he covers ~16' in one second:

 

Note: Click here to watch the demo on IPVM

For example, if you only have 1 frame per second, a person can easily move 4 to 16 feet in that time frame. We need to keep this in mind when evaluating frame rate selection.

 

We cover:

 

    • What speed do people move at and how does that compare to frame rates.

    • Walking: What risks do you have capturing a person walking at 1, 10 and 30fps.

    • Running: What do you have capturing a person running at 1, 10 and 30fps.

    • Head Turning: How many more clear head shots do you get of a person at 1, 10 and 30fps.

    • Playing Cards: What do you miss capturing card dealing at 1, 10 and 30fps.

    • Shutter speed vs Frame Rate: How are these two related?

    • Bandwidth vs Frame Rate: How much does bandwidth rise with increases in frame rate?

    • Average Frame Rates used: What is the industry average?

 

Walking Examples

 

As our subject walks through the FOV, we view how far he moves from one frame to the next. In 30 and 10 fps streams, he does not complete a full stride. However, in the 1fps example, he has progressed ~4' between frames, which falls in line with our measured walking speed of ~4' a second.

 

Note: Click here to watch the comparisons on IPVM

 

 

Running Examples

 

With our subject sprinting through the FOV, the 30 fps stream still catches him mid stride, while in the 10 fps stream, he has traveled ~1' between frames. In the 1 fps example, only one frame of the subject is captured, with him clearing the rest of the FOV between frames, with only his back foot visible in the second frame.

 

Note: Click here to watch the comparisons on IPVM

Capturing Faces

 

Trying to get a clear face shot can be difficult when people move because they naturally shift their head frequently. In this demonstration, we had the subject shake their head back and forth walking down a hallway to show the difference frame rate plays.

 

Take a look:

 

Note: Click here to watch the demo on IPVM

 

 

Notice, at 1fps, only a single clear head shot is captured, but at 10fps, you get many more. Finally, at 30fps, you may get one or two more, but it is not much of an improvement.

 

Playing Cards

 

In this test, our subject dealt a series of playing cards from ace to five with the camera set to default shutter speed (1/30).

 

In the 30 and 10 fps examples, we can see each card as it is removed from the top of the deck and placed on the table. However, in the 1 fps example, we see only the cards appearing on the table, not the motions of the dealer, as frame rate is too low.

 

Note: Click here to view the comparison samples on IPVM

 

 

Shutter Speed vs Frame Rate

 

Frame rate does not cause blurring. This is a misconception. The camera's automatic shutter speed control does.

Dealing cards ace through 5 again, we raised the camera's minimum shutter speed to 1/4000 of a second. The image below compares the motion blur in the dealers hand and card, with the 2 card much more easily legible in the fast shutter speed example.

 

 

 

1/4000s shutter speed completely eliminated all traces of motion blur. 1/1000 and 1/2000 of a second shutter speeds significantly reduces blur, but it was still noticeable around the dealers fingers and edges of the cards when looking at the recordings frame-by-frame.

 

If you have blurring, you have shutter speed configuration problem, not a frame rate one.

 

Slow Shutter and Frame Rate

 

On the other side, sometimes users want or camera manufacturers default their maximum shutter to a rate slower than the frame rate (e.g., a 1/4s shutter for a 1/30s camera). Not only does this cause blurring of moving objects, you lose frames.

 

Key lesson: The frame rate per second can never be higher than the number of exposures per second. If you have a 1/4s shutter, the shutter / exposure only opens and closes 4 times per second (i.e., 1/4s + 1/4s + 1/4s

+ 1/4s = 1s). Since this only happens 4 times, you can only have 4 frames in that second.

 

Some manufacturers fake frames with slow shutter, simply copying the same frame over and over again. For example, if you have 1/15s shutter, you can only have 15 exposures and, therefore, 15 frames. To make it seem like you have 30 frames, each frame can be sent twice in a row.

 

Be careful with slow shutter. Beyond blur, you can either lose frames or waste storage.

 

Bandwidth vs Frame Rate

 

Frame rate impacts bandwidth, but for modern codecs, like H.264, it is less than linear. So if you increase frame rate by 10x, the increase in bandwidth is likely to be far less, often only 3 to 5 times more bandwidth. This is something we see mistaken regularly in the industry.

 

The reason for this is inter-frame compression, that reduces bandwidth needs for parts of scenes that remain the same across frames (for more on inter and intra frame compression, see our CODEC tutorial).

 

Illustrating this point further, we took 30, 10 and 1 fps measurements to demonstrate the change in bit rate in a controlled setting in our conference room. The average bitrates were as follows:

 

    • 1 fps was 0.179 Mb/s

    • 10 fps, with 10x more frames, consumed 4x more bandwidth than 1 fps (0.693 Mb/s)

    • 30 fps, with 3x more frames, consumed double the bandwidth of 10fps and, with 30x the frames, 7x the bandwidth of 1fps (1.299 Mb/s)

 

These measurements were done with 1 I frame per second, the most common setting in professional video surveillance (for more on this, see: Test: H.264 I vs P Frame Impact).

 

For more on this, see our reports testing bandwidth vs frame rate and 30 vs 60 fps.

 

Average Frame Rates Used

 

Average industry frame rate is ~10fps, reflecting that this level provides enough frames to capture most actions granularly while minimizing storage costs.

 

 

 

As shown in the previous section, going from 10fps to 30fps can double storage costs but only marginally improve details captured.

 

For more commentary on why integrators choose the frame rates hey do, see the Average Frame Rate Used Statistics report.

Bandwidth

 

 

Bandwidth is one of the most fundamental, complex and overlooked aspects of video surveillance.

 

Many simply assume it is a linear function of resolution and frame rate. Not only is that wrong, it misses a number of other critical elements and failing to consider these issues could result in overloaded networks or shorter storage duration than expected.

 

We take a look at these factors, broken down into fundamental topics common between cameras, and practical performance/field issues which vary depending on camera performance, install location, and more.

 

Fundamental Issues

 

    • Resolution: Does doubling pixels double bandwidth?

    • Framerate: Is 30 FPS triple the bandwidth of 10 FPS?

    • Compression: How do compression levels impact bandwidth?

    • CODEC: How does CODEC choice impact bandwidth?

    • Smart CODECs: How do these new technologies impact bandwidth?

 

Practical Performance/Field Issues

 

    • Scene complexity: How much do objects in the FOV impact bitrate?

    • Field of view: Do wider views mean more bandwidth?

    • Low light: How do low lux levels impact bandwidth?

    • WDR: Is bitrate higher with WDR on or off?

    • Sharpness: How does this oft-forgotten setting impact bitrate?

    • Color: How much does color impact bandwidth?

    • Manufacturer model performance: Same manufacturer, same resolution, same FPS. Same bitrate?

 

Scene Complexity

 

The most basic commonly missed element is scene complexity. Contrast the 'simple' indoor room to the 'complex' parking lot:

 

 

 

Even if everything else is equal (same camera, same settings), the 'complex' parking lot routinely requires 300%+ more bandwidth than the 'simple' indoor room because there is more activity and more details. Additionally, scene complexity may change by time of day, season of the year, weather, and other factors, making it even more difficult to fairly assess.

 

We look at this issue in our Advanced Camera Bandwidth Test.

 

Resolution

 

On average, a linear relationship exists between pixel count (1MP, 2MP, etc.) and bandwidth. So for example, if a 1MP camera uses 1 Mb/s of bandwidth, a 2MP camera on average might use ~2Mb/s.

 

However, variations across manufacturers and models are significant. In IPVM testing, some cameras increase at a far less than linear level (e.g., just 60% more bandwidth for 100% more pixels) while others rose at far greater than linear (e.g., over 200% more bandwidth for 100% more pixels). There

were no obvious drivers / factors that distinguished why models differed in their rate of increase.

 

As a rule of thumb, a 1x ratio may be used when estimating bandwidth difference across resolution. However, we strongly recommend measurements of actual cameras as such a rule of thumb may be off by a lot.

 

Frame Rate

 

Frame rate impacts bandwidth, but for inter-frame CODECs such as H.264, it is less than linear. So if you increase frame rate by 10x, the increase in bandwidth is likely to be far less, often only 3 to 5 times more bandwidth. Illustrating this, we took 30, 10, and 1 fps measurements to demonstrate the change in bit rate in a controlled setting in our conference room. The average bitrates were as follows:

 

1 fps: 0.179 Mb/s

    • 10 fps: 0.693 Mb/s (10x the frames of 1 fps, but only 4x bandwidth)

    • 30 fps: 1.299 Mb/s (3x the frames of 10 fps, but only double bandwidth. 30x frames of 1 fps, but only 7x bandwidth)

 

(These measurements were done at 1 I frame per second with quantization standardized ~28.)

 

For more detail on frame rate's impact on bitrate, see our Frame Rate Guide for Video Surveillance.

 

Compression

 

Compression, also known as quantization, has an inverse relationship to bandwidth: the higher the compression, the lower bandwidth will be.

CODECs

 

A key differentiation across CODECs is supporting inter-frames (e.g., H.264, H.265) vs intra-frame only (e.g., MJPEG, JPEG2000).

 

    • Inter-frame CODECs such as H.264/265 not only compress similar pixels in an image, they reference previous frames and transmit only

the changes in the scene from frame to frame, potentially a large bandwidth savings. For example, if a subject moves through an empty hallway, only the pixels displaying him change between frames and are transmitted, while the static background is not.

    • Intra-frame only CODECs encode each individual frame as an image, compressing similar pixels to reduce bitrate. This results in higher bandwidth as each frame must be re-encoded fully, regardless of any activity in the scene.

 

For more on inter and intra frame compression, see our CODEC tutorial.

 

The vast majority of cameras in use today, and for the past several years,

use H.264, due to its bandwidth advantages over MPEG-4 and Motion JPEG.