Hey! Sriram here, author of this work. I'd be glad to answer any questions. There's also a short talk I gave about this here (https://www.youtube.com/watch?v=t4Txdhlji4k) if that's helpful!
Yes, we do! There are a couple of user-facing annoyances at the moment, one of which I mentioned in another comment (hacks to align the color and ToF images). Hopefully these API limitations are removed soon, or we find better workarounds.
I would love to, but I'm not sure how yet without a major re-write. The augmented reality code we completely rely on is part of Google Play Services for AR. I definitely do understand the benefit of degoogling, so maybe it can be a community effort once I opensource it.
Man, we're so bad at naming, that we keep joking about it... And trying to satire that with internal codenames (the ones engineers give without adult supervision)... And somehow those often seem better than the external names :(
It could also possibly work on iOS, but there's a catch we have not yet explored. We're relying on something called the "confidence" score in the ToF camera API, which has 8 possible values (3 bits) in Android, but from what I last saw, has only 3 possible values total in iOS. It's not clear how this lack of info exposed by the APi will affect accuracy.
This is something we'd have to separately test, and ultimately make a wholly different app for if it's feasible on iOS.
There's no reason it has to be worse. It's good development practice to design your system to loosely couple with dependencies you have no control over. Worst case you could have two versions, and the one that supports google services works better for whatever imagined reason.
Is there a support group or discord for degooglers? I did it a month or so ago and am still dealing with the ramifications. Most recently I used App Warden to disable all the spyware libs (including Google's) shipped with WeChat. They detected this, and banned my 10 year old account with all my friends and relatives. Been struggling for two days trying to get it reactivated, cuz it will be extremely difficult to travel back to China without it. I am not blind to the irony of keeping Tencent on my phone as I remove Google.
What would be really helpful is a database of apps, similar to the WINE project, maintaining how well they work on a de-googled phone, with a table, columns being "no root", "rooted", "with microg", etc, and a WINE style rating of how well it works and what problems you'll run in to.
You would know which banking services, etc don't work well or at all and could choose your establishments with foresight.
There is a GitHub repo[1] with a very limited list last time I checked. That the best I could fined in my degoogled time.
The Techlore Youtube-Channel-Community (yes, I realise the irony) also seems like a reasonably healthy place to start.
There is also a bunch of telegram groups with NoGoolag[2] at the center. I would not recommend for the 70:30 mix of conspiracy and tech support but they are at least technically very knowledgeabl, and sometimes helpful, even considering their almost 'religious' technical beliefs.
Sorry I'm not aware of anything like this. I went "all in" : I just installed GrapheneOS on my phone, Linux on my desktop and stopped using anything Google related (except YouTube that I watch in a dedicated browser).
Interesting question. Mainly as mentioned above we needed Google Play Services for AR. Nothing else stands out at a high level.
However there is a clear bottleneck with the Google AR team for features that the community really wants. While it's understandable, perhaps the open source libraries aren't the priority or there's short staffing, there are issues like this one - https://github.com/google-ar/arcore-android-sdk/issues/153 - that have been open since Jan 2018. This one asks that we can use the smartphone flashlight simultaneously with ARCore, but there's no visibility on how close we are at the moment. This feature would have likely improved our work's performance greatly, but even in general, many other AR developers are asking for it.
Re: overcoming it, there's not much we can do in this case. We just didn't implement the feature.
I apologize Sriram I actually I meant to ask that to the user jmnicolas who asked you to for de-googled application; Yet you provided valuable information.
Long standing issues/feature requests are typical of Google's Android ecosystem, Regardless I eagerly await for your release. I think ToF based spy-camera detection could make a great addition to the women safety apps in India.
Sadly no project-specific page yet, but I'll definitely update on my page at https://sriramsami.com/research/ (I think there's an RSS feed?) when it's active.
It's easy to set up a mailing list. Just sign up for mailchimp, or any one of the many newsletter products like substack or tinyletters, just to collect the email addresses. Not many people regularly read RSS anymore, sadly.
It's definitely something I'm considering. The only hard blocker now is a hashmap that checks for our test phones' unique ID and applies a fixed transform to align both cameras. Right now, any other phones will cause an immediate crash. Minimally I think we need to disable this and maybe include a small UI to let users put in the alignment parameters (just a scale + offset).
Also I appreciate the interest, thank you. I'm heading back from the conference over the next few days, so I should be more free to take a look at it soon.
Thats very interesting, first time hearing of it. Not sure, really depends on what kind of reflection it generates when light hits it, and because of the unique design I'm not sure what that will be.
> many early "stealth" radar detectors were equipped with a radar-detector-detector-detector circuit, which shuts down the main radar receiver when the detector-detector's signal is sensed, thus preventing detection by such equipment.
Well if the hidden camera can be shut down by turning on a hidden camera detector, then the hidden camera detector becomes a hidden camera jammer! All the better.
What are the properties of the cameras that don't get detected? Wouldn't bad actors just use the same app to check if their cameras are detectable at installation time?
So far the biggest issue is if the camera is angled oddly away from the user (basically, outside the 20 degree observable FoV). Another issue would be if they manage to install a larger camera that returns larger reflections (which we filter out).
Regarding using the app to check, I guess that applies for the existing handheld detectors as well. It's definitely something that intelligent attackers can try to plan for, but we havent tested the adversarial robustness of the system right now. That would be a very interesting direction for us as well.
While this work operates on ToF sensors that are already present in smartphones (e.g., Samsung S20+/Ultra), a Microsoft/Azure Kinect should also be a valid option because it has a depth camera as well. It has a higher resolution and bit-depth as well.
We initially intended to compare against the Kinect, but it doesn't fit the use case (something that you can have on you at all times). However, it could be a cheap choice for a different kind of deployment (automated hidden camera detection with robots, perhaps?)
So I had no idea phones have ToF sensors these days. Do most phones have them or only the high-priced flagships? What are the actual intended uses for them?
High priced flagships have them but there are also a few midrange phones like the Huawei P30 Pro that have them too. The trend seems pretty positive towards more ToF sensors in phones, especially because Apple has had them for two iPhone Pros in a row now.
They're basically for augmented reality applications because they sense depth. Placing objects at the right size and scale in the augmented view is much easier and more accurate with the ToF sensors, for instance.
Any phone that has sub 200ms focus times has to have some sort of TOF sensor, right? The Asus Zenfone 2/3 laser, the Huawei monochrome sensor on the honor series, the portrait and/or macro sensors on the Xiaomi mi note 10, whatever the original Zenfone had, and so on.
Not all of them are lasers, which might be important.
I don't think so. There's "laser-assisted autofocus" which might be slang for an actual ToF sensor, but sometimes that's just a single laser pulse (I.e., no 2D image that we need).
I was wondering if cameras started using anti-reflective glass would this prevent detection? Some of the glass I’ve looked up say they reflect less than 1% of light. How sensitive is your app could it detect 1% reflections? Thanks
Yep, the combination is highly reflective. I cited another work (by a physics research group) in a comment that modelled and tested this effect comprehensively.
Would you speculate if anti reflective glass on the outside of the camera and a layer of one way tint on the inside that would allow light through but prevent it from reflective back out? I’m just thinking what we will expect in the future to sell the “undetectable spy camera”.
That's a great question. I'm not totally sure if this is possible. If it was, I think one-way mirrors would use this technology. For now, it seems like they only work because they only let 50% of the light through + there's a brightness differential between both sides. Perhaps someone more informed about this could chime in.
Yeah, there's no magic material that can violate the second law of thermodynamics, because it's the second law of thermodynamics. One-way mirrors are just partial mirrors with less light on one side than the other.
Then they'd have a signature of reflecting less than surrounding. In the long long run, probably more robust to detect the entropy generated by computation in a physical area (i.e. heat) and not the optics.
Agreed. I expect however that any easily available thermal sensing, especially on smartphones (see FLIR, etc), could be easily defeated with a strong adversary doing good thermal management.
As you say though, extra heat is a physical guarantee, so maybe a smarter technique exists to separate signal from noise in the thermal domain that I don't know of yet.
So would something like anti reflective glass for light coming into the camera then another layer of like tint that will stop light from reflecting back out if the camera? Ya I know that doesn’t exist but That is because they were not trying to do undetected as hard before. Just thinking of counter surveillance techniques.
While the broader technique should work for those applications, the platform (smartphone ToF sensors) probably won't. Smartphone ToF sensors have a pretty limited range. We were only able to detect cameras within 1 metre of the smartphone because we're really using the hardware for something it's not intended for.
For the applications you suggest, there are some existing military-looking devices out there that use multiple lasers to find sniper scopes, for example. My basic searching shows at least https://www.ldsystems.us/product/sniper-optics-detector/#, though I'm sure there's more.
- Increasing the resolution of ToF cameras (right now images are around 320 x 240) --> reflections from hidden cameras can then be more detailed, whereas now it's only 1 or 2 pixels each.
- Increasing the bit-depth of ToF images - right now every pixel is only 3 bits (8 colors). It's very hard to differentiate bright hidden camera reflections from everything else, so we had to do a lot of work for that.
- API improvements in conjunction with augmented reality libraries, e.g., a) allowing Android devs to enable the flashlight when AR apps are running b) more raw access to the ToF sensor if possible
Samsung started marketing their ISOCELL Vizion 33D camera in 2020 with 640 x 480 resolution. So it's likely we'll see better ToF resolution announced in some phones in the next year or two.
Thank you! Actually, my understanding when I started this project was that I would get a 640 x 480 image (IMX516 sensor). However, I could only get a 320 x 240 image from the sensor through the Android API, so that was a bit of an oddity.
Hm, if "ToF sensors" are LiDARs.. why does only Apple market them as LiDAR? Why are all the "3D scanning" apps only for Apple's "Pro" devices? How come no one knows that some Android devices can do the same things? I didn't know until this thread!
My understanding is that not all ToF sensors are LiDARs. There are also different types of LiDARs, e.g., some of them scan the environment and others just emit a single beam in the same one direction. I think iPhone Pro has the scanning one, but I haven't read much about it.
I assume one is active while the other is not. With two cameras you have the option of stereoscopic analysis where you have to match pixels of two cameras looking on the scene from a different angle. That uses significant cpu-time though, difficult for real time applications. Results vary because the matching isn't trivial and the difference in angle in smartphone cameras is very low.
If you have a projector, you can do more. I believe Apple uses a flash, which has a low resolution, but is perhaps less cpu-intensive and less error prone, although it has a lower resolution. That would be a real Lidar, which is an active measurement. Of course combining that with sensible stereoscopy nets better results.
There's a lot of marketing involved in this naming, with Samsung calling it DepthVision and Apple calling it LIDAR. There may be a difference here, however. My understanding is that Apple LIDAR is doing what we call "direct" ToF, where the round trip travel time of laser pulses is actually measured (this can be in nanoseconds). This lines up with what self driving car (and other expensive) LIDARs do.
Most other ToF sensors use "indirect" ToF, where they measure the phase difference between incoming and outgoing signals to derive distance.
However, it gets murky as cheap 2D LIDARs on say, robot vacuum cleaners, use geometric techniques to find distance (basically return angle of a reflection). I explored this in a previous work.
TLDR: I would recommend not taking any naming at face value and reading the actual datasheet or more commonly, technical marketing materials, since few ToF manufacturers that I see have a public datasheet.
"Specifically, the hidden camera [...] reflects the incoming laser pulses
at a higher intensity than its surroundings due to an effect called
lens-sensor retro-reflection. This occurs when almost all light energy
impacting an object is reflected directly back to the source"
Likely. Headlamps are well known tools for collecting spiders at night, when positioned just right they will reflect off the spider's eyes as you move your head around. It's an amazing thing to see spiders everywhere.
Can vouch for this having heard the theory and tried the "torch at eye-level" method and been able to zero-in on small spiders from a distance of about 5m.
It's quite amazingly effective, especially the first time, when you're not really convinced.
This is actually one of the recommended methods if you have no other options. It's not particularly good otherwise because of the limited visibility cone of the hidden camera reflections. From experience, the flashlight often tends to occlude the reflections you want to see, or the user isn't in the right place to see the reflections (near the flashlight).
Agreed, and a very valid point that these off the shelf detectors are pretty cheap compared to ToF smartphones. There are a number of unfavourable things about the detectors though:
- No automated detection, so lots of human subjectiveness on whether a bright spot should be investigated
- Background lighting can be an issue, so the view through the detector can be filled with bright reflections
- When I tried this for longer than 30 seconds, there's really some eye strain involved
The idea is that the smartphone has more than this one purpose, and the detection system can improve with software updates, whereas you get what you see with the detector and nothing more.
The light returns pretty directly to the source which is why most devices designed to use that detection method have the illuminators around an eyepiece so there's less distance between the illuminators and your eye.
This reminds me in a way of the yacht with a system that detects cameras taking a picture of the yacht and sends a beam towards the camera to wash out the image.
Pretty interesting idea. In fact, there are a number of military-related systems to spot sniper scopes (generally optics) with lasers, which I expect is similar to what they used here.
that kickstarter campaign is borderline a scam. They have an msrp of 400$ for a Chinese gadget you can by for <10$ online. And no, their LEDs are not special and you can source better ones from digikey for less than 1$.
It's not a "scam" if people buy it and it works. There is the cost to design such a thing. It's not free. The unit price was high. The rest are knock-offs who didn't have to pay for R&D.
Then you can make and sell your very own one using their effort.
the knockoffs were widely available online (ebay/amazon/aliepress/DX) for a decade before this kickstarter existed.
The kickstater itself is a cheap knockoff that didn't bring any new feature or any new design elements. I was too lazy to do the research, but it wouldn't surprise me if they just rebranded a product offered on alibaba.
I would support them if they offered a superior design with a nice looking aluminum/Stainless/titanium case, made it more compact, or made it waterproof, etc. but they did nothing like that. They are offering the same cheap back plastic design that looks 95% like all the other cheap chinese knockoff.
Great question about the angle actually. There's previous work by an applied physics group [1] that shows the detectable field-of-view from the camera is about 20 degrees. Our experiments also confirm that.
We also think using the smartphone flashlight (if that's what you mean) is the best way forward. That's already very helpful (and recommended) for humans to find hidden cameras, and it should be a useful extra modality for our work too.
You don't have to answer but, I'm assuming by the phone's API you can steer the beam/have an exact precision known of the minimum angle you can sample? That's pretty cool tech to work with.
Unfortunately we can't steer the ToF beam, so the user has to move the phone around to multiple positions (a 2D grid of positions, basically). The app provides pretty clear guidance on where to move the phone to cover all possible spots, though.
Yep, there are a pretty decent number of smartphones with it, and I think the trend is moving in the right direction (iPhone 12 Pro had it and Apple included it in the iPhone 13 Pro too).
Yeah I guess my phone is not in that tier... it looks to be marked up 2x from GSMArena's prices... but $150 vs. $350 pricing. Also the Moto G Stylus (my phone) is from 2020
Maybe, but realistically, since the sensor uses the properties of a camera lens to detect the camera itself, I would have to bet there is little that could actually be done to obscure the hidden camera and also still get a usable image from it. This is a pretty brilliant detection method.
It might be easier to design the room to create false positives and undermine trust in the detectors. Assuming you have that kind of influence, anyway. That's not an option if you're just trying to plant a camera in an existing room.
I assume minimizing the aperture would be a fairly reliable way to avoid detection. A pinhole camera would be hard to find by any optical technique, though the video quality would suffer. Perhaps one could project through a pinhole onto a screen and record the projection, so the sensor is angled away from the room?
That's an interesting idea: trying to create so many false positives that the user gives up. We're already removing around 100+ false positives per frame at the moment in difficult cases, so perhaps it's possible to overwhelm the filters with very maliciously designed environments.
I think the easier way would be to hide the cameras in much harder-to-reach places so that it's inconvenient for the user to get their smartphone near. This might reduce the kind of videos that can be taken, but maybe an attacker will find that a reasonable tradeoff.
Probably the very smart spy camera can detect off axis TOF artificial light and close a shutter over the lens. Assuming your app integrates over the scanning motion, the camera won't be detected while it's shutter is closed. After the illumination is completed the spy camera can re-open it's shutter.
The spy camera could also something like your system to detect the phone camera and take defensive measures.
Security is always an arms race. Making the person hiding the cameras make the extra effort is worth it because some will be too lazy. Also some wont know and be caught which increases precieved risk which may tip the risk-reward scale more towards risk for the person hiding the camera making it less likely they would decide to try.
I was working on a project like this and we relied on the fact that the IR filter on most cameras was a retro reflector. Remove the IR filter and the camera will be harder to find. I think the technique here also depends on the IR filter’s characteristics.
That's a good point. I'm not sure how the removal of the IR filter will affect this work. I mentioned some prior work from the physics side [1] in another comment that explores the reflection characteristics in more detail. I don't think they explored the IR filter contribution as well, so this could be an interesting direction.
We were trying to detect audience members filming at live events and in movie theatres, esp. premieres and film festivals (and this was some time ago, when studios, etc, cared more about this). It worked pretty well, even in the early 2000s. I suspect you could do much better today with some "AI" behind it.
IR cut filters used in smartphone-style cameras are typically reflective.
Installing an absorptive IR cut filter on top of the lens would decrease the amount of reflected light, and might hinder your approach. Those are pretty cheap to buy, so you could try it out pretty easily.
> Specifically, the hiddencamera embedded in the object reflects the incoming laser pulses at a higher intensity than its surroundings due to an effect called lens-sensor retro-reflection. This occurs when almost all light energy
impacting an object is reflected directly back to the source (see Section 2.2). These unexpectedly high-intensity reflections from hidden cameras cause certain regions of the ToF sensor to be “saturated” and appear as black pixels. LAPD processes these saturated areas to automatically identify the hidden camera and its location and displays it on the user’s smartphone screen.
Nevertheless, if you block all the ~850nm IR light from reaching the lens, then there cannot be any retro reflection at this wavelength, meaning the ToF cannot see anything.
Yes, I agree. I believe military-grade optics detection systems use multiple wavelengths, and some even use short bursts of visible light, making it harder to block.
If there was literally ANY metric I would want in a HUD; 'How many cameras are viewing me now, and where are they' has got to be the top of the list...
A stand-alone Single-Point LIDAR might be used to remove the high-end phone requirement. Should interface to a phone USB port with a simple UART/I2C-USB adapter.
Search Amazon.com for LIDAR finds 'Lidar Range Finder Sensor Module TF-Luna, Single-Point Micro Ranging Module 0.2 to 8m Compatible with Pixhawk, Arduino and Rasppbarry Pi with UART / I2C Communication Interface' $25.
And 'MakerFocus TFmini-s Micro Lidar Module 0.1-12M Lidar Range Finder Sensor Obstacle Avoidance Sensor Tiny Module 1000Hz Single Point UART I2C IO Compatible with Pixhawk Ar duino and Raspberry Pi' $39.
The 2nd one is waterproof.
Also on Amazon 'Worldoor CC308+ Multi-Detector Full-Range All-Round Detector For Hidden Camera / IP Lens/ GMS BUG / RF Signal Detector Finder , CC308 + detector hidden mini camera/IP camera/general manager/radio frequency signal detector instrument' <$20.
And several similar hidden camera detectors.
I have no idea how well/badly this sort of device works.
I would be curious to know what would be the best method/tool to detect hidden cameras in places you visit (e.g. hotels, AirBnBs). I looked for devices on Amazon.com and found nothing that seems to be really good at detection.
Funnily enough this is exactly how we started the project, just with a different Thinkpad model.
Separately, Lubos, the creator of ToF Viewer, is very helpful to the ToF community and constantly answers any questions about APIs or sample code. I'd recommend talking to him if anyone wants to get started with ToF-based applications.
I wonder how hard it would be to engineer a material that you can put on top of the hidden camera lens that would greatly diffuse the specific frequency range of light that these ToF sensors use while permitting mostly visible light through? If so, it might be possible to defeat this approach relatively easily.
Looking at what the DL filter is doing, I wonder how well this really generalizes. It seems that many of those examples are virtually indistinguishable to a human (hence the high false positive rate for the naked eye experiments).
w.r.t the material, it seems to be possible, since ToF sensors operate in a narrow 850 nm band. However, I don't know if a coating can be made that also doesn't overlap with the visible light range since 850 nm is somewhat close to red light, or whether that would be cheap if so (given that the hidden cameras themselves are only $1 at the moment).
I also have similar reservations about the DL approach in general. What makes me more confident is that we trained on a relatively small number of objects (~10) and tested on a totally different set of 30 objects. We're also using very small regions-of-interest as inputs (5x5), so there's little to no overfitting on the environment or objects themselves.
If the spy camera has infrared leds then you can detect those by removing the infrared filter from a camera, can be done on some smartphone cameras programmatically I think.
In a dark room, you can point an old-style remote control at an iPhone camera and see button presses light up the IR transmitter.
I do this to test their batteries :)
But older Cell-phones (flip phones) with CMOS sensors used to be really good at this as they wouldn’t filter much IR in order to work better in low-light conditions.
It hard to tell if these modules contained IR interference filters, some of the part numbers are only for sensors not modules. If they have interference filters I could see that there would be a strong IR reflection. It would be interesting to see the results with a absorptive filter, although I am guessing real spy cameras have no filter at all. Improve the sensitivity vs making a pretty picture.
I'm having a hard time seeing how the obsolete and not exactly tiny OV2640 was crammed into that electrical plug. The integrated module is a 10mm cube with a 1/4" lens and to be useful it needs a power supply and either a storage controller or wireless network interface.
We just used the OV2640 module itself (https://www.aliexpress.com/i/4000036275403.html) which is pretty small. While we didn't actually include a little battery and perhaps something like an ESP-32 to control it, I'm pretty sure those could fit inside the plug if hollowed out.
"Tiny hidden spy cameras concealed in sensitive locations including hotels and bathrooms are becoming a significant threat worldwide." I think motel room tenting and indoor foil-wearing might seem to be more justifiable, less paranoiac. Who knew?
Hey! Author of the work here. We just finished presenting this at a conference yesterday, so we're working on open-sourcing the code now with some feedback from the community. It's got some warts because of API limitations (no way to automatically align color and ToF cameras, so we're manually doing that).
You'll still need the laser emitter. Here I would hope the emitter can be operated in a high-power small-target mode to also obliterate the detected cameras. Extra points if it can do so autonomously - I leave it over the bed, go out for dinner, and come back to a room without any cameras.
I'm not sure that it's a conclusive yes here. We have a procedure to remove the effects of background reflection saturation by constantly analysing the maximum reflection size. So if there's a large reflection in the scene, we walk the user back til we have all reflections at the same size or smaller than the the larger expected hidden camera reflection. This works fairly well.
However, if the camera reflection is always within a larger reflection for all possible distances and angles, then I doubt this will work.
Issues are with AirBNB and shady landlords. Sometimes people being pervs, but also just extortion. You can create an AirBNB listing wither hyper restrictive rules, spy on your tenants, and then charge them fines after the fact.
I see. Makes sense. Are such airbnb experiences common, though? Given other controls such as reviews, are they expected to be long lived? I could maybe see the harm caused to a few individuals, which is deplorable, but once a single extortion event happens the expectancy of income is reduced.
Anecdotal, but my partner recently went to a lake house for an engagement party. The lake house is a touristy location, and obviously meant to be a vacation home. However, the renters would only list the property as a "meditation retreat." Meaning no alcohol, no noise, no day guests, no fun. They had beach chairs in an unlocked area, and after the weekend sent a $900 bill to the guests. Apparently even though the chairs were freely accessible, using them constituted rental, so they charged $50 per chair per day. How else did they the host know they used the chairs that many times if they were not spying on them somehow? I imagine if they actually did anything, that bill would have been higher.
Wonder if some rules and ... oh, regulations? would create a situation where the renter would not have to worry about issues like this. Perhaps similar to rules and regulations that ... hotels have?
That is not the best analogy, because I assume less risk at home than elsewhere. My question was about the threat, and since adversaries are not installing cameras in people's home your comment does not answer my question.
Of course, frequently. I must still be missing something. I have had zero extortion requests. My footage might be captured for private consumption by some perv, but where is the harm to me?
Extortion is generally geared towards women. Violence towards women like this is a general negative externality/tax on society because everyone interacts with women.
I am inclined to agree, and you are correct if you assume that I am male. But I would prefer to see the data. Without it, the first sentence of the abstract is unsubstantiated. "Tiny hidden spy cameras concealed in sensitive locations including hotels and bathrooms are becoming a significant threat worldwide." The paper cites no evidence for "significant threat worldwide". Academic fancy?
That is a good question, and thanks for helping me to test the limits of my argument. I would say that voyeurism, like all crime, can be expected to follow a spatiotemporal probability cloud. Society does not accept folks peering into your home and as an individual you have recourse. I think it is fuzzier as soon as you step out into public. I would definitely consider an airbnb or most other spaces that are outside my control to be public spaces. But the question of voyeurism is sort of distinct from my main question, which is how big is the risk? Do we have data on how many people are hurt by this issue?
Same issue, but thank you for trying for an alternative. I’ll skip this one; it may be wise be wary of a website so adamant about cookies that they refuse to show any content when they don’t get them.
The free option: use your smartphone's flashlight and try to spot unnaturally bright / colored reflection.
If you want to spend some money and don't mind carrying an extra device: probably any of the "hidden camera detectors" on the market will be at least somewhat useful. K18, CC308+, etc.
We're trying with our work to get better or at least equivalent results without having to use external devices.
I don't think this works, mainly because an extremely bright external source of 850 nm light looks incredibly suspicious through the sensor (as we expect the ToF sensor to be the only light source). We could add that check in explicitly.
I think the bright light is intended as a countermeasure to the hidden camera, not as a countermeasure to finding the hidden camera.
Basically, to keep position X unobservable through the hidden camera, ensure that there is an overwhelming source of photons between position X and the hidden camera.
Since we don't know where the hidden camera is, the best we cam do is to assume that the immediate vicinity of the bright light will accomplish this.
Oh, I must have misunderstand, since the root comment was talking about detection methods. But yes, jamming is a good option, and there have been papers to make areas "unrecordable". I don't have my citation manager on hand now, but I think it was an early ACM Sensys / Mobisys research work.
I know a woman who discovered a hidden camera in the female toilet at work disguised as some kind of utility hook on the door. Cheap to buy on amazon!! The SD card inside had pictures of the company owner's desk but not an actual picture of him. The police declined to prosecute because of lack of evidence.
Contrary to popular believe, circumstantial evidence is not bad evidence. In isolation, it might not be enough to convict, but when used in conjunction with other evidence, it can create a damning case.
1. The camera contained pictures of owners desk.
2. That model camera was purchased on amazon by the owner.
3. The serial number of the camera indicates that it was sold on amazon and produced around the time of purchase by the owner.
4. The camera was found in a place the person had reasonable, unrestricted access to.
5. owner was found in possession of pictures that look to have been taken by the device, in the position where the device was originally discovered.
* I'm not asserting these facts are true, just stating them for the sake of example.
In isolation, each of these pieces of evidence don't prove much, but in totality, it is highly unlikely that all of those things would happen to an innocent person. Jury's don't need to be 100% certain to convict, they need a preponderance of evidence.
I can see why a prosecutor wouldn't pursue this case against a rich person though. The police are unlikely to do a good job at collecting evidence, a good lawyer will get enough of it thrown out, victims probably won't want to testify anyway, and being a business owner, this person might have clout with local politicians who will make trouble.
It's interesting with these wrap head lamps, which have 40 COB(Chip on Board) LEDs, is you see spiders everywhere at night. And other large animal eyes with a Tapetum lucidum look 'strange', not like normal led reflections.
It's a bit unnerving/cool that you'll see 10 pairs of eyes looking back from the lawn you might have just been lying on.
You have to go to the second page of the full PDF to even see what LAPD stands for, which is Laser-Assisted Photography Detection. They need to be more mindful of this, especially when they made up the acronym themselves.
I don't think you should argue this :
No idea what RCMP stands for without a google search.
I got RAF from the context (I assume you mean Royal Air Force ?), but without context I would map it to other things.
And I have no assumption about the meaning of LAPD
The authors are from Singapore. The association is not that direct for non-americans. Actually, I only noticed it after several people mentioned it here.
