Expectations From Security Cameras

Set Realistic Expectations

Some people think that Neighborhood security surveillance is a silver bullet that will solve all problems related to crime. It is not, it is but one step in a neighborhood crime fighting initiative.

What to expect in regards to Prevention

Visible signs of Security Camera activity, such as signs and visible cameras, has a measurable preventive effect on premeditated crimes like burglary, robbery and theft, but has absolutely no preventive effect on crimes of passion like public drunkenness and fights.

Video Surveillance improves crime solving rates under certain circumstances.

Example of incorrect use of surveillance cameras.

The public surveillance cameras Tiburon, Ca, installed February 2010, has only contributed slightly to crime solving, the main problem being that the cameras are placed in High traffic areas. Specifically the problem is that when examining cameras recordings, the suspect pool becomes too big to of any practical use.

Quiet neighborhood streets are perfect

Low traffic areas or areas with low traffic of suspects have a better chance of isolating suspects and therefore solving the crimes. The quiet suburban street – a burglar favorite – is also the place that has the best return of investment for a neighborhood camera solution, especially when combined with individual alarm systems.

Does footage always lead to conviction? 

No – most of the video produced will be considered circumstantial evidence, e.g. images of  the suspect entering and/or leaving the neighborhood around the time of the crime, will help in the investigation and together with other pieces of evidence will lead to a conviction.

What footage is needed for Conviction.

In order to get a burglary conviction based on surveillance video alone the video will need to have all of the following:

  1. 100% certain identification: i.e. clear unmasked face shoot
  2. The breaking and entering.
  3. The suspect leaving with items of value that are clearly identifiable.
  4. Clear chain of evidence of the footage.
  5. Timestamp on the video
  6. Video obtained without violating the suspects constitutional rights. (see article on legal considerations)

Example of footage not enough for conviction alone.

The following photos is not enough to convict by itself.

  1. Suspect arriving on the street, license plate readable
  2. Suspect entering the driveway of victim
  3. Suspect leaving the driveway of victim 10 minutes later.

It is however enough for an investigator to pay a visit to the suspect, and if we are lucky the suspect is on probation or parole letting any peace officer in California perform a warrantless and suspicionless search and seizure.

If the same vehicle and person has been linked to other burglaries it could be enough for a search warrant and/or an arrest.


Don’t expect that the police can rush out and make an arrest based on your video surveillance, do expect that submitting your video to the police could be the lead that changes a case from unsolvable to solvable leading to apprehension of the criminals.

Don't expect the Police to make an arrest based on your images alone. Actual Camera recording of Police Car at 3:00 am with one of our Cameras, click to zoom in and read the license plate.

Additional reading

Parole and Probation searches – Article – Police Magazine

Burglar shoots at witness

Oakland Police is asking citizens and neighbors to review their video footage in relation to a burglary that escalated into a shooting, morning Friday April 27, 2012 at 10:00 am.

3 young men in a Black Chevy Trailblazer burglarized a house on Thornhill drive between Armour Drive and Snake Rd.

The occupant left the house shortly before 10:00 am and burglars entered the house around 10:00 am leading to speculation that the burglars had had the house under observation waiting for the occupants to leave.

During the quick burglary an Ipod, Ipad, and jewelry was taken.

Contractors working nearby observed the burglary shortly after 10:00 and called the Police. As the burglars were leaving they saw the witnesses and shot at them, hitting their car. Police records the shot a fired at 10:17 am. The Oakland Police responded with 3 units.

The Police is looking for License plates and images of the vehicle and occupants, from anyone with a camera pointed at Snake Rd. (Unfortunately our cameras are not pointed at Snake Rd.).

Police reports that the vehicle description matches descriptions from other burglaries in the area.

Here is the sparse news coverage:


Decoy Cameras

  • Now that we have invested in a really expensive camera how do we avoid that the camera itself gets stolen?
  • Will the criminals learn to avoid the cameras?
  • How about vandalism?
  • If we hide the expensive camera won’t we lose the preventive effect?

These are all excellent questions.

The solution is to hide the real camera and setup visible cheap decoy cameras.

Both real and fake cameras has a proven preventive effect on premeditated crimes!

The more cameras the more prevention.

Only the real camera will catch the criminal.

The $5 Camera looked like a cheap Toy

Once mounted the $5 camera looked like a cheap Toy (click for larger image)

By using the right combination of hidden expensive cameras strategically placed and visible cheap decoy/fake cameras, neighborhoods can achieve a cost-effective combination of prevention and apprehension.The first decoy camera we tested cost only $5 on amazon including shipping, it looked good in the photo, but the real thing looked like a cheap-toy.

Dome camera over front door

Dome camera is ideal for the front door (click for larger image)


The next camera tested was a $20 (now only around $5) dome style camera, it looks pretty realistic, and is ideal for indoor use and for above the front door installation. But for giving the impression of surveillance of public spaces it is not the right type.

The Dome Camera is recommended for Personal use, and can be ordered from amazon here: SE Dummy Security Camera, Dome Shape, 1 Red Flashing Light

The right Decoy Camera

The Real Surveillance Camera next to the Decoy - can you tell which is which?

The Real Surveillance Camera next to the Decoy - can you tell which is which? (click for larger image)

3rd time was the charm, the camera we got was a high quality plastic mold of a real outdoor surveillance camera costing around $10.

At that price it is worth putting up a lot of cameras.

You can buy the Decoy Cameras online from Amazon in single or in bulk.

  1. 1 pcs Outdoor Fake Dummy Security Cameras LED Blinks Camera
  2. 2 pcs Outdoor Fake Dummy Security Cameras LED Blinks Camera
  3. 4 pcs Outdoor Fake Dummy Security Cameras LED Blinks Camera
  4. 10 pcs Outdoor Fake Dummy Security Cameras LED Blinks Camera

Ideal placement.

The decoy cameras come with a short cable that goes into the wall mount, in your mind you have to determine where this cable is going. If you place the decoy on a tree or a light pole then you have to add a fake cable that goes away from the camera. The easiest solution is to place the camera on a wall where there it would be natural to run the cable on the other side of the wall. Don’t hide the decoy camera, but instead make sure that it can be clearly seen from the street and make sure it has a good view of the street/intersection.

=============== UPDATE May 13, 2014 ============================

Advice from Captain Jeffrey Israel, Oakland PD, place the camera in a place where it is lit and seen at night, e.g. in an area lit by an outdoor light or motion detector security light.

The well placed camera is mounted on a wall that can accommodate the cable while being visible and having a clear view of the street

The well placed camera is mounted on a wall that can accommodate the cable while being visible and having a clear view of the street. (click for larger image)

 Blinking LED or not.

All the decoy cameras above has a LED and a battery compartment for a 9 volt battery.
A 9 volt battery will last about 3 months before needing replacement.
We turn OFF the blinking LED on the real camera, a blinking red LED will make a camera very visible at night. So the question becomes:

1) “If the real camera does NOT have a blinking LED, will giving the fake cameras a blinking LED make them look fake?”
2)  “if the neighborhood is not on its toes in regards to changing the batteries, you will create a situation where some of the cameras will have a blinking LED and some will not, will this make the all cameras look more fake?”

You will have to find that answer yourself depending on how likely your group will be running out with ladders every 3 months to replace all the batteries.

Neighborhood Camera Starter Kit

Last Updated Novermber 25,2014.

The most common question I get is: Which camera are you using?

The Camera is only one part of the equation, power and lighting are very important factors.

Here is the Starter Kit for less than USD $2,000 (subject to small fluctuations, be sure to use the links below to ensure that Amazon contributes to Neighborhood Guard)

Neighborhood Security Camera Starter Kit

Rugged Swedish Outdoor 5 megapixel Camera Axis P1357-E 5MP/HDTV (1080p+)
Power Over Ethernet Camera Power supply. Alfa 48V IEEE802.3af PoE Injector, Power Over Ethernet Adapter
Ethernet Cable out to the camera CAT5E, UTP, Bulk Cable, Solid, 350MHz, 24 AWG, Black, 1000 ft
Connectors for the Cable 100 pcs Cat6, Cat5E Crimp Connectors
Cable Strain Relief RJ45 Black Strain Relief Boots (50 Pcs Per Bag)
Connector Crimp Tool New RJ45 CAT5 Network Lan Cable Crimper Pliers Tools
Black Spray Paint for Camera Rust-Oleum 249127 Painter’s Touch Multi-Purpose Spray Paint, Flat Black, 12-Ounce
Camouflage for Camera Polyester Leaf Ghillie Helmet Cover Camo Woodland
Mounting Bolts Galvanized Steel Lag Bolt, Hex Head, 5/16″, 1-3/4″ Length (Pack of 10)
Infrared Illuminator CMVision IR100 – 98 LED Indoor/Outdoor Long Range 200-300ft IR Illuminator With Free 2A 12VDC Adaptor
Long Low-voltage Power Cable for the Infrared Illuminator Coleman Cable 095136208 12/2 Low Voltage Lighting Cable, 100-Feet

We are trying to negotiate a bulk price for our members, until that is finalized please use the links above as it will get you the best prices available and make a small donation back to Neighborhood Guard.

Question from a Neighborhood Guard Member:
If we install 2 cameras, does the original order have enough ethernet cable, connectors, relief boots, mounting bolts, and low voltage cable for both cameras?

For Each Camera and Infrared light you will use:

  • 1 x Run of ethernet cable from your router to the Camera. (max 300 feet)
  • 1 x Run of low-voltage cable from weatherproof/Indoor wall outlet to camera. (Max 200 feet)
  • 2 ethernet connectors
  • 2 ethernet relief boots
  • 4 mounting bolts


Video of Burglar leads to arrest

A couple of days ago there was a burglary attempt at a neighbor – The incident was caught on a Security Surveillance Video.  The Video shows 3 young men approaching a house, then running away from the house once the alarm is triggered and speeding off in a ordinary looking silver sedan.

Suspects fleeing attempted burglary after triggering Alarm

3 days later I got this email from the Captain of the Police in Oakland.

OPD is happy to inform you that the suspect in the burglary video (and responsible for numerous break ins and attempted break ins in the hills) is in custody. I will release more information when I can and doing so does not compromise the investigation.  I sincerely appreciate all of the fantastic assistance from the community on this crime series. There is no doubt that without community support these crimes may not have been solved yet.


Jeffrey Israel

Captain of Police

Oakland Police Department

It once again show that having Video evidence moves the crime to the top of the solveability list.

Thank you Oakland Police and thank you video surveillance.

Man walking dog shot in Oakland hills last night.

A man was shot last night @ 10:30 while walking his dog on Elverton (1st road north of Snake road) in a part of Oakland hills far from the high crime areas of Oakland.

He had just returned to his front yard when his dog started barking, and he saw two young men approach in hoodies. They said, “hold it there”, then threatened with a gun, when the victim turned and ran to his house he was shot.

The shot penetrated his arm and broke the bone, which is lucky, considering that the perpetrators was probably not aiming for his arm.

Police response time for 1 of the 3 responding officers has initially been given as 20 minutes by a neighbor to the shooting. (I am trying to establish how long it took for the first Officer to arrive)

The Elverton neighborhood has a video surveillance group, they are currently assembling their footage.

When a violent crime happened in our neighborhood last year we decided as a group that:

Never Again, will a violent criminal enter or leave our neighborhood undetected.

This Blog is to show that it is possible to put up resistance when criminals terrorize your neighborhood, as long as people come together and stand united.

=================== UPDATE APRIL 18, 2012 =========================

Oakland PD’s Captain Israel has sent me the following timeline of the police response, showing a quick and appropriate response from Oakland Police:

10:35 pm              crime happens
10:39 pm              victim calls OPD Dispatch
10:40 pm              three officers (lights and siren response) and paramedics are assigned to the call – victim is met and provided emergency medical treatment for his wound at the scene
11:05 pm              another officer is assigned to meet the victim at the hospital per the field supervisor (victim was transported via ambulance).

I had a good talk today with the Investigating officer. He told me that based on the facts, the  case is treated as a an assault with a firearm as defined in California’s Penal code section 245, and not as a Robbery under section 213.

The Elverton neighborhood watch video group did capture the vehicle of the shooters. But unfortunately only on an older analog system that could not provide a clear night image of the vehicle’s license plate. Please subscribe to this blog via the front page to learn how our group managed to capture license plates in the darkest part of the night.

Another video system in a different part of town did catch an image of a suspect but the image was lost due to a 3 day video retention policy, and the investigating officer didn’t learn about the recording until the fourth day. This just goes to show the importance of a long image retention policy.

=================== UPDATE APRIL 28, 2012 =========================

The first officer at the scene arrived 10:56 PM -17 minutes after the 911 call.

With the current Police staffing situation in Oakland, we cannot expect the police to arrive in time to catch the Criminals, we need to have a system that can clearly identify perpetrators, day and night.

Picking the best photo and Motion detection.

When the camera records a sequence of images, some of images are going to show the approach and one image are going to the vehicle large and centered. I want to pick the  image where the vehicle is best seen so that 1) I can use it to best represent the sequence on an overview page 2) can feed a few good images to a potential License plate recognition software.

Purple box around picked image.

In the sequence to the left, the images around the middle of the sequence gives us what we want. So why not just pick the middle image.

Picking the middle image in the sequence will produce the right image in 70% of the cases.

Problem 1 with picking a photo at a certain position in the sequence is that these photos might work well for vehicles travelling in one direction, but will be completely wrong in the other direction. (Neighborhood recording one-way streets are in luck)

Problem 2: Changing the Motion detection sensitivity will completely change any setting based on position in the sequence.

Problem 3: middle image in a sequences that contains 2 evenly spaced vehicles will show the empty road between the two vehicles.

The question: is it possible to programatically a) select the right photo every time and b) determine when there is more than 1 vehicle in the sequence and split the sequence into two or more sequences, one for each vehicle.

To do this we have to not only look at motion detection but to determine where the moving object is in the photo and then pick the photo where the object is the largest without being partially out of the frame.

The first internet search took me to this fine page, where I found this algorithm

	h1 = Image.open("image1").histogram()
	h2 = Image.open("image2").histogram()

	rms = math.sqrt(reduce(operator.add,
		map(lambda a,b: (a-b)**2, h1, h2))/len(h1))

The algorithm is quite popular and quoted many times on the internet when there is talk about comparing images.

What is does is comparing image histogram and returning a single number showing how different the images are, with 0 meaning the images are identical.

Hey piece of Cake! I just have set a threshold value and when the difference is biggest the car is biggest in the photo….

Lets see how that worked in real-life:

  1. The difference between the 1st (empty road) and 2nd image is low  (<10) – so far so good
  2. As the car approaches the difference to the 1st photo increases – (50, 65, 85) hey I am onto something
  3. As the car is right in the middle of the picture the difference between the empty road and the photo is 535  – This might actually work
  4. As the car is leaving the picture stage right the difference drops to 462 – still on track
  5. Now we have empty road again and the difference is 437 – hey wait this is wrong. How can two pieces of empty road be as different as if there had been a minivan in one photo?

The RMS Difference between these two images is as much as if there had been a big minivan in one of the images

.If you look carefully you can see a slight shade difference between the two images. the Sun moved …. (it has a tendency to do that).
Loading the images into Photoshop and examining the histograms, I can see that the histogram is almost identical but shifted between the images.

After hours of playing with the above algorithm, I can conclude that the algorithm is really good at detecting changes to a photo such as adding text or manipulating a small block of the photo, but it is useless at detecting differences between two scenery photos, because the scenery is constantly changing.

The next algorithm search took me to examining the difference function in the Python Image library (PIL). Again the the entire picture is different ;-(, but reducing the number of colors, and the resolution caused me to generate this image of a minivan, with all the changes contained within the box.

Box outlining the changes in the photo.








From there I made the current algorithm which is pretty good for a first attempt.

#compare current image with Master and make a box around the change
diff_image = ImageOps.posterize(ImageOps.grayscale(ImageChops.difference(master_image, cropped_img)),1)
rect = diff_image.getbbox()
if rect != None:
	ImageDraw.Draw(cropped_img).rectangle(rect, outline="yellow", fill=None)

I highlight the detected area of change on the original thumbnail to easily determine effectiveness.

Yellow box highlights the are of the detected vehicle

Hmm,I detect the roof, the front bumper, then larger and larger parts of the vehicle, there is definitely room for improvements here.

This is as far as I currently am on detecting the vehicle inside the image, but check back for my next attempt at cracking this algorithm.


Alarm + Community Security Cameras is the best thing since sliced bread.

During my work on the Neighborhood Security Camera work I had an epiphany that I need to share:

Having an Alarm makes your Neighborhood Security Cameras 10 times more effective.
Having a Neighborhood Security Camera Program makes your Alarm 10 more effective.

Let me explain:

Alarm alone: it will have a slight deterrent effect on Crime, and with a police response time in our area measured in hours, absolutely no effect on apprehension.

Neighborhood Cameras alone: if advertised well it will have a deterrence, but with a regular burglary on a property without alarm the time window of the crime will be too great to be useful to the police. “I left early this morning and when I came back tonight we had been burglarized, so it was one of the 200 cars that passed the Camera between 7:00 am and 6:00 pm. The local police will put this case at the bottom of the pile, with a solveability factor of next to nothing.

Neighborhood Cameras and Alarm:
Alarm was triggered at 1:43 pm, camera has 1 unknown car going into the neighborhood at 1:38 pm and leaving at 2:02 pm. we have the license plate. Police solveability is high, and it will go to the top of the pile, hopefully leading to recovery of personal property.

It really makes perfect sense once you think about it 😉


Collecting Trusted License Plates

One of the problems with having a Neighborhood video surveillance system is the number of unknown vehicles that show up on any recording.

For any such system to be valuable, the neighborhood group managing the system has to filter out the trusted vehicles in order to locate the suspicious vehicles.

Inherently trusted vehicles

The Firetruck is inherently trusted

The Firetruck is inherently trusted

Some vehicle comes with a certain level of trust based solely their apperance:

  • Police cars
  • Ambulances
  • Firetrucks
  • Garbage Trucks
  • Cement Trucks
  • Fedex
  • UPS
  • USPS

Not so trusted vehicles.

At the other end of the scale are vehicles that are suspicious just because they don’t fit the standard of the neighborhood: This could be because that they are too expenses, too flashy, to loud, too fast, too slow, too colorful, too dilapidated, too old. etc.

The bland majority

Between these two poles are a large number of vehicles that are just ordinary: these are the cars that the bad guys choose when they want to blend in.

On a typical day we have more than 100 unique such cars passing our camera. The only way to be able to distinguish the good cars from the bad is by having a list of trusted license plates.

If you live in an area without garages or with a shared parking structure, the task can be accomplished by just walking with a camera phone a couple of times.

However if you, like us, live in an area were many people park their cars inside garages you will have to engage the owners. The good news is that this actually increases security awareness and the feeling of community, core features of a good Neighborhood security group

  1. Start by sending out emails asking people for License plates
  2. then send out 1 or 2 more nagging emails to get some more addresses.
  3. Finally make a list of all the addresses where you are still missing the licenses and go door-to-door asking people to open the garages.

Where to record the vehicle information.

Some people will find that putting car model/make and license plate on your neighborhood roster makes them uncomfortable.
Most people find that having a trusted vehicle list that is independent of the Roster and is only accessible by a small group of trusted neighbors is the way to go.
Many people will volunteer color, Make and Model in addition to the License plate, some will only give you the license plate. Some will volunteer extra information like year, accessories (like roof-rack and stickers). A good system will have a way to capture this information.

For most group the list is so simple that it can be kept in a single spreadsheet, however if you have more than one person viewing and updating a file based sheet, you will have a hard time making sure everyone has an updated copy

We found that using a hosted shared spreadsheet was the best solution, and are currently using the free Google Docs spreadsheet.


Traffic Count and Statistics.

Cute little garbage truck captured in the fog, one of 8 passings of garbage trucks that day.

Our Neighborhood Security Surveillance Camera records a lot of traffic but how many passers-by do we really record:

I decided to pick 1 day and do a detailed count, this happened to coincide with a theft from a car that night which allowed me to combine the work.

in 24 hours, the motion detector recorded 491 sequences of events on 1 camera covering an entrance to our neighborhood.
The count below records objects passing the camera, not unique cars passing, e.g. the same car coming and going will be counted as 2.
1 Bicycle
2 Motorcycles
3 Utility trucks
7 Delivery vans
8 Contractors
8 Garbage Trucks (garbage day, but I was surprised it was that many)
14 Pedestrians (with 6 dogs)
238 Passenger Cars
1 Suspicious Person (Photo and license plate submitted to Oakland Police)

Total of 281 relevant events.

The rest was false alarms on the motion sensor, e.g.  moving shadows from clouds, fog, changing light. (it was a foggy day)  e.g.

License plate readability
Of the 266 vehicles, 7 did not have a License plate. (2.6%)
Out of 259 vehicles with License plates 255 could be read by human(*) (98.5%)

(8) The human is me, method included selecting the best photo for each vehicle and using different zoom levels, sometimes part of the license plate could be read in one photo and the rest of the plate in another photo. No image manipulation was needed (such as Photoshop)

Room for Improvement
A motion detector False Positive rate of 42% – is too much.

While I would rather have too many recordings than missing 1 critical, here is room for improvements.
I am currently adjusting the sensitivity levels in order to try reduce the number of false recordings.