When we first introduced our iCVR, I heard from a number of other video analytics companies. They offered their compliments. Many of them said that when a new market is gaining recognition, all successful products help bring growth to the whole field, so it was good for everyone. I was glad to hear them say that, because I feel the same way. It is nice to work in a field where there is open communication and friendly compliments, even though we are competitors.
But the one area that they thought we’d gone too far with was our marketing message that our product needed no tuning or calibration.
I said, “Well, it’s true.”
They looked at me in a way that it made it clear they didn’t believe it was even remotely possible. They were thinking this was going to be another case of a company over-exaggerating their claims. That’s one of the worst things for new technologies, since it hurts credibility and people start doubting any of it works.
I reassured them that our claims were true, no matter how hard it was to believe. In fact, I said, even if someone wanted to, there is no way for an installer to tune or calibrate our iCVRs. That’s when they realized we really meant what we said.
For some people, our claims sound too good to be true. In fact, only a few months ago, Itsik Kattan, CEO of Agent-VI, said in an article: “Beware of ‘low-touch’ and ‘no-touch’ systems and vendor claims that their analytics self-learn. There’s no such thing.”
Lately, the language we’ve been hearing has created even more confusion. Some sales people are saying that calibration and tuning are required to get high accuracy, and any system that doesn’t use calibration and tuning are on the order of traditional video motion detection.
We’ve also heard from some who promote the idea that the more tuning knobs the better, and some products have more than 50 different adjustments that can be made. They feel they have the best accuracy as a result.
There are some serious flaws with these comments. However, the real problem here is that this kind of talk focuses on the wrong thing.
It isn’t about whether tuning and calibration can help make a system more accurate. We agree that it does. It’s hard to argue with that. The real question is which is better: Automatic self-tuning and calibrating systems, or manual systems?
We’ve got plenty of tuning going on in our iCVR. The moment it starts up it learns the environment, adjusts the filters is it using, and continues to get smarter over time. As the environment changes, it re-tunes and continues to adapt.
The calibration process also happens automatically. The iCVR watches for people and vehicles and boats, and when it sees them it automatically calibrates what the proper height for these objects should be. This does indeed reduce false alarms, although it doesn’t help our systems as much as it helps other technologies.
The reason we can do the calibration automatically is because our accuracy before calibration is far better than any other product. If accuracy is poor to begin with, then you have to use manual calibration, because the system doesn’t know what objects are people and which objects are false alarms, like tree branches or birds or bushes blowing in the wind.
In fact, the worse a technology is to begin with, the more important calibration and tuning is. Take advanced video motion detection (AVMD) systems that don’t even know what a human looks like: They are far more dependent on calibration and tuning than true video analytics systems. Why? Because AVMD doesn’t have any way of knowing it is a person except by the size of the object. Manual calibration is the only way of teaching the system what a human should look like.
Of course, AVMD even with calibration and tuning doesn’t even come close to true video analytics systems, as I’ve written about earlier on this blog.
But let’s get to the big issues that make this issue so important. Here are the advantages of a self-tuning and self-calibrating system:
- It saves hours of set-up time per camera. We’ve heard the average is between 3-8 hours per camera. That’s significant.
- You don’t need specially trained technicians to install it. Anyone who knows how to install a camera can do it. The more tuning knobs a system has, the more important it is to train every installer to get the best results. No tuning knobs means that anyone can install it.
- You don’t need to re-tune or re-calibrate every time a camera is moved. The system adapts automatically (note, if you set up detection for a specific region of interest, you may need to change the region of interest, which is why our system automatically tells you if a camera has been moved). For manual systems, if you don’t re-tune and re-calibrate, you are assured that the system is set up wrong after the camera is moved.
- If the environment changes, the system automatically re-tunes itself. When the leaves fall off the trees or when snow appears on the ground, you can be assured that re-tuning is needed to improve performance. But with manual systems, unless you manually re-tune it when the seasons change, you will have degraded accuracy and more false alarms.
- Self-tuning and self-calibrating systems are always at their best. Manual systems are at their best the minute after you tune it and calibrate it. After that, performance deteriorates. With our iCVR, performance actually gets better over time.
- Lastly, we are continuing to improve the performance of our analytics. Every time we do, we provide a downloadable update that can be sent to all the iCVRs in the field, thus improving their accuracy. But with a manual system, how do you send new algorithms and use the old tuning settings? With new algorithms, you need new tuning adjustments. So, it is a much more time consuming process to update to the latest improvements.
When you add all of these issues up, I don’t know how you argue that manual adjustments are better.
But the whole thing still comes down to how accurate the system is. Having an automatic technology that has poor detection and high false alarms is not going to be an improvement.
So, where does our iCVR stand?
When compared against the best of the best video analytics technologies, even if you bring in an engineer from their factory to do the tuning and calibration so you know it is absolutely adjusted the best it can be, from what we’ve seen and heard, we are about on par and maybe slightly better. In some cases we’ve seen that we beat them, but we’ve seen a few cases were they edge us out by a hair.
But that is the moment after tuning and calibration. Our system then continues to get smarter and more accurate, while all the manual tuning and calibration systems get worse. So, over time, we have the clear advantage in terms of accuracy.
We’ve had plenty of people test our stuff and have confirmed this, but it is always best to try this out for yourself and come to your own conclusion.
However, I think the rest of the benefits make the point pretty clear. The cost to install and maintain, and the ease of use are all in favor of systems that are smart enough to calibrate and tune themselves.
In other words, there really isn’t any controversy here.
