Difference between revisions of "Understanding ZoneMinder's Zoning system for Dummies"
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====Pixels or percents?====
====Pixels or percents?====
What makes more sense to you? "Raise an alarm if
What makes more sense to you? "Raise an alarm if are changed" or "Raise an alarm if more than 20% of my zone has changed?". To me, the latter makes much more sense.
So I've always used percents
So I've always used percents
====Right percents. But what values?====
====Right percents. But what values?====
Revision as of 12:05, 11 March 2019
ZoneMinder has a powerful zone detection system using which you can modify how sensitive, precise, accurate your motion alarms are. The official ZM documentation does a good job of describing all the concepts here. However, you will see gobs of posts in the forum about people complaining that ZM logs all sorts of events (ahem, as did I), ZM's detection is rubbish and in-camera is better (ahem, as did I) and what not. But once you get the concept, its incredibly powerful.
So instead of giving you a theoretical explanation, lets walk through a live use-case. (Credit: user kkrofft helped a lot in me getting a hang of things here. You should also read his earlier explanation here)
Let's take a look at this area below. Lets suppose you want to trigger motion if someone tries to break into your basement. Does it make sense you monitor the full area (pillars/walls/floor)? Probably not. If someone were to break in, they'd break in from some door, some window, or maybe break in from upstairs and climb down the stairs. So doesn't it make more sense to monitor these areas specifically? I think so. So the first 'common sense' logic is delete the default zone that ZM creates for each monitor (which is called All). Monitoring every part of your image may make sense if you are monitoring and outdoor lawn, for example. Not here
Defining the zone areas
So given the explanation above, how about we define zones where motion matters? Any zone you define as "active" is what ZoneMinder will analyze for motion. Ignore the 'preclusive for now'. So lets look at the image below. I've defined polygons around places that are the "entry points"
Okay, now how do I specify the sensitivity of the zones?
ZoneMinder has pre-sets. We live in a world of pre-sets. I bet you want to select "Best and highly sensitive" don't you? DON'T. Not because that setting is nonsense, but because you should understand some concepts first.
The ZM wiki I pointed to earlier does a great job of explaining different methods. At the cost of repeating what has already been said, its important to note:
- ZM does NOT understand objects. It only understands pixel colors. So if you are monitoring a camera that is producing a 1280x960 32bit color depth image, as far as ZM is concerned, it is getting an array of 1280*960*32 bits of data to analyze and compare a previous frame and based on 'color differences' between frame X-1 and X along with some algorithms it applies in addition to color differences, it tries and guesses if objects (in ZM speak, a specific pattern of pixels) have come up that were not there previously.
- ZM has 3 methods of detection: Alarmed Pixels, Filtered Pixels and Blobs. Here is a visual explanation of their differences
The first image is a 20x20 grid. Let's assume this is a zone. And the black circle is some object in this grid. The second image shows the next frame of that image, where new 'objects' have appeared, or in ZM's view 'new sets of pixel patterns'
Now let's talk about Alarmed Pixels, Filtered Pixels and Blobs
Alarmed pixels only deals with pixels changes. If we use the alarmed pixel method and specify a minimum of "5 pixel" changes (lets forget max for now), then all the new pixels of set A + B + C + D will count as alarmed pixels and the total alarmed pixel count will be A+B+C+D
Now let's assume we used Filtered pixels and set it to 2x2 pixels. The in addition to computing the alarmed pixels (A+B+C+D), it will also count how many of these sets have at least 2 pixels around them that are also alarmed pixels. This will result in B+C+D (set A will be discarded as they don't have any pixels surrounded by at least 2 pixels that have changed color from the prev. frame)
Now lets assume we used Blob and said a blob needs to be at least 10 pixels. Then what it will do is based on the set computed by Filtered pixels, which is B+C+D it will look for contiguous blobs of 10 pixels and that only means D
So, in Alarmed pixels any of A, B, C or D would raise an alarm In filtered pixel mode, only B, C or D would raise an alarm In blob mode only D would raise an alarm
Okay, that was a simple explanation. And I did not cover more details on min/max. But I hope you get the core idea..
Yawn. Forget the theory. Let's get back to your basement image
Okay, back to my basement and my 3 zones.
Which detection type should I use?
I personally feel to detect "humans", blob is the best. As I described above, it combines Alarm + Filtered + ensures that the pixel differences are contiguous and then does an algorithmic analysis to see if it forms 'blobs'
Pixels or percents?
What makes more sense to you? "Raise an alarm if 178 pixels are changed" or "Raise an alarm if more than 20% of my zone has changed?". To me, the latter makes much more sense. So I've always used percents (Updated in 2019: Given a lot of people seem to refer to this article, in some cases, it does make more sense to use pixels, especially if the difference in sizes is small. Example: its not possible to visualize the difference between 10% and 15%)
Right percents. But what values?
- Zones and Depths: One of the learning for me was that don't make zones cover a lot of depth as far as the camera lens goes. Why? Well take a look at the image above. As a person or a pet walks away or towards the camera, it gets significantly bigger or smaller (right, that was not rocket science, but sometimes commonsense 101 helps)
- Percent vs. Pixels: Back to my previous point -if you specify alarmed areas in pixels, in addition to being able to visualize better (at least for me) the added advantage is the setting scales as zone sizes changes. For example the % of space the person takes in my far end "Door" zone is quite similar to the % of space the person takes in my couch area (in other words, both the zone and person have scaled up in size, so relative % is still the same)
- So having said all of this, this is what my zone definition for the "stairs area" looks like:
Lets see how ZM will use these values:
- Use the "blob" method to detect movement (which means first use Alarmed pixels, then use Filtered Pixels, then use Blob)
ZM's motion detection algorithm for this zone:
- Set A = full zone pixels
- (Min/Max Pixel Thres) In the *Full* area defined by the zone, check if there are any pixels that have have a 40 count difference in pixel color from a previous. Assign to Set B. If Set B = null, don't raise alarm, don't proceed with rest.
- (Min/Max Alarmed Area) check if Set B is at least 6% of Set A and not more than 75% of Set A. If Set B does not fall in this range, don't raise alarm, don't proceed with rest.
- (Filter Width/Height) In the set of pixels (Set B) that are different in color value of 40, check if there are pixels that are surrounded by 5 more pixels around them that are also different in color value of 40. Assign to Set C. If Set C = null, don't raise alarm, don't proceed with rest
- (Min/Max Filtered Area) check if Set C forms at least 4% of Set A but no more than 75% of Set A. If Set C does not fall in this range, don't raise alarm, don't proceed with rest
- (Min/Max Blob Area) use Blob logic on Set C to figure out how many Blobs are there. A blob that is at least 4% in size of Set A (full pixels) is considered a blob. Assign this to Set D.
- (Min/Max Blobs) - If the # of blobs in Set D is less than 1, don't raise an alarm, don't proceed with rest
- Raise Alarm!
Note the percentages I describe above seem lesser than the visual percentages when you look at the image. First, my image is not to scale. Second, I guess I could increase the percentages, but these values are working quite well for me, but in reality I guess I could easily increase, say, 6% to 10%. In general, I'd recommend using the least value that is not triggered by small things - keep raising it till you stop getting 90% of spurious alarms, but no further. If you try and eliminate all spurious events, then its likely you will also miss some valid motion (that's a non scientific anecdotal statement, so feel free to challenge me here)
Here is my zone setting for the door (Edit note: the max alarmed/filtered area was changed to 70% - the image shows 90%)
The logic is similar to the foyer area - plus, I've used the overload frame count -- basically the sun blasts through the blinds and in those cases the % change is very large (around 75+%) which triggers my max % spec and in that case, I tell zoneminder to ignore the next 2 frames so that this excessive lighting condition does not raise lots of alarms. BTW, this is one zone where I still get 4-5 false events in a day. I am fine with it and prefer to live with it.
Ah, I get it. But hey what's that preclusive zone in your image at the start of this artlce?
Ah, ZM allows us to specify a zone where should an alarm occur, it suppresses alarms in that zone and all other zones in the monitor. I've set it to cover my recess lights. So if someone turns our lights on, I won't get an alarm. Does it work? Yep pretty well. Does it always work? Mostly. Heh heh.
Some other optimizations
There are other optimizations you can do. Another setting I found useful is to use "Alarm Frame Count". This is not part of Zones, but part of your monitor definition (Buffers tab). It specifies the minimum amount of alarm frames to trigger an alarm. Most of my cameras are on Wifi and my basement is farthest away from my AP, so I occasionally get smearing. Setting this to 3 reduces almost all smears raising an alarm
You're a dork. None of this mumbo jumbo worked for me. I want my money back
Life sucks. Take a break. Drink a glass of wine. Or two. Then get back to your settings. And its possible these don't work for you - try different values. Think visually. Oh, and I'll need a postage paid envelope to email you a $0 cheque. And a $5 cheque from you to pay for gas to drive to the nearest post box. Labor is free because you did not like my article. There is a lifetime return policy, you see.