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Category: Cameras / Photos / Video

Video chat’s next major feature: physical positioning of participants (“mingle at a party” options) to allow a huge chat to be split into manageable groups!

Background:

With the 2020 COVID plague, work-related video chats have become increasingly full of a large number of participants (Figure 1).

Fig. 1: Video chat software (e.g. Zoom, FaceTime, Hangouts, Meet, Duo, Skype, and more) typically only allows participants to appear in a randomly-ordered grid. All participants are part of the same (single) discussion: there is no easy way to have a “side discussion” and then rejoin the main conversation.

The issue:

Video chats have a problem that in-person office work does not: there is no convenient way for participants of an unreasonably-large video chat group to split off into subgroups.

Instead, every discussion must take place in a SINGLE mega-discussion with all participants, or people need to leave the mega-discussion and start their own exclusive video chat groups. People often get around this by having side discussions over text, but that’s not really a great solution either.

Proposal:

In a physical workspace, it’s easy to have a small discussion: simply PHYSICALLY relocate the individuals in the conversation to an empty lunchroom table or meeting room.

To improve video chat, we simply implement the same feature: instead of each video participant just being a randomly-placed square in a grid, now each participant can also specify their location on a virtual floor plan (Figure 2).

Fig. 2: Left: the old-fashioned style of video chat. Right: the updated video chat, where you can only hear and see participants who are in close physical proximity. In this case, the chat has split into groups A, B, and C (shown here from the perspective of a person in Group B). Everyone in Group B has a normal video chat, but can only faintly hear low-audio-volume chats going on in groups A and C.

Importantly, it’s still possible to see and hear people who are somewhat nearby on the floor plan, but at a very low volume. So you can know that a conversation is going on, and join in if necessary, but it won’t drown out your primary discussion.

Previous Examples:

Some video games implement a system like this (“proximity audio”), in which you can hear voice chat only from nearby players. However, as far as I am aware, this has never been a feature in any office-focused collaboration software.

PROS: This seems like it should actually exist! Maybe it hasn’t been developed before due to the lack of compelling business case for having large numbers of people on video calls.

CONS: Might lead to a tyrannically oppressive workplace in which work-from-home employees are mandated to always be available on video chat and present on a virtual floor plan.

Never be concerned whether or not your household electronics are spying on you! This new repurposing of the “ON AIR” sign will save you from fretting!

Background:

It seems that nearly every electronic device with a camera or microphone is now Internet-enabled and can wirelessly send video and audio to the world.

The issue:

Due to the preponderance of electronic hardware in a modern household, it can be difficult which (if any) device is spying on you at that exact moment (Figure 1).

This is a relatively new phenomenon, since it used to be the case that:

  1. Cameras were relatively large
  2. Non-CIA recording devices generally needed to be physically wired to a power source and network cable.

Fig. 1: One of these devices is currently streaming video from the user’s house—but which one? Video-enabled devices sometimes have a recording light (but not always: e.g. phones, tablets), but checking these lights is still annoying and time-consuming. And audio recording generally has no indication whatsoever!

Proposal:

The classic solution to the “are we recording right now?” question is a lit-up “ON AIR” sign [see examples] that can light up whenever a TV station is broadcasting.

This same concept can be applied to modern devices: a person would buy a new piece of “ON AIR” hardware (this would essentially just be a WiFi-enabled screen). This ON AIR sign would connect to the household WiFi network light up any time it detected video being sent out to the Internet.

Detecting that streaming is happening could occur in two ways:

1) Network traffic analysis can generally identify data as “this is a stream of video / audio.” This is a solution that would probably work in most cases.

2) Each video/audio-enabled device can talk to the ON AIR sign over WiFi and notify it that streaming is occurring. This would be on the “honor system”: well-behaved software would periodically report that it was streaming. One benefit of this opt-in method is that streaming devices could send additional metadata: e.g., instead of just “ON AIR (Some computer is sending video),” the user would see “ON AIR (Joe’s PowerBook G4, streaming video over RealPlayer for 4:34)”.


Fig. 2: Thanks to this lit-up “ON AIR” sign, the user knows that there is some device recording them, and exactly which device is responsible (in this case, the “smart television”).

Of course, neither of these methods is a 100% guarantee of detecting live video being streamed: for example, a phone that was using its cellular data to stream would not be detected.

Conclusion:

This could probably be a legitimate product!

PROS: Would be a good value-add option for a router manufacturer. “This router will light up if it detects outgoing video/audio!”

CONS: Might cause the user to become extremely paranoid upon realizing that their watch, tablet, computer, phone, external monitor, fitness tracker, headphones, and dozens of other devices could all be surreptitiously spying at any time.

Don’t get on another video chat until you’ve fixed your crazy mountain-dweller hair with this incredible “green screen wig” lifehack!

Background:

When on a meeting with video chat, people generally like to look at least vaguely professional / presentable, even if they just rolled out of bed 5 minutes before the meeting.

The issue:

There are two main problems in video chat for people who want to project a corporate-approved professional image:

  1. The background should look non-disastrous.
  2. The person taking the call should not look like they have been living in a cave for weeks (Figure 1).

Several videoconferencing applications have solved problem #1 by adding a “virtual green screen” feature, which can automatically transform the user’s messy room into an expensive-looking modern mansion interior (e.g. the house from the movie Parasite).

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Fig. 1: This videoconferencing individual may be harshly judged for their unkempt appearance. If only there was a technical solution to this (besides using a comb)!

Proposal:

Fortunately, we can use the exact same green screen technology to allow the user to fix up their hair situation.

The implementation is simple: the user wears a cut-out green screen “hat” (Figure 2) that allows the computer to superimpose a flowing mane of magnificent hair behind them. Hair problem: solved!

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Fig. 2: The head-attached green screen could be secured in place by a hairband, or it could be glued to the front of a pair of headphones.

PROS: Should save millions of hours per year in hair maintenance for videoconferencers.

CONS: May promote a new standard of unrealistically majestic hair.

Throw away your laptop privacy screen and use this camera-plus-software approach for the ultimate in security!

Background:

Laptop privacy screens (or “monitor filters”) reduce the viewing angle of a laptop screen in order to prevent evildoers from snooping on sensitive information on your laptop (Figure 1).

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Fig. 1: Since this laptop does NOT have a privacy screen on it, the suspicious individual at left is able to view this contents of the laptop (despite being at an extreme off-center angle).

The issue:

Unfortunately, these privacy screens have a few downsides:

  1. They are inelegant to attach. Often, the attachment points block a small amount of screen real-estate.
  2. They slightly darken the screen even when viewed directly head-on
  3. When collaborating with coworkers, removing and replacing the screen is time-consuming.

Proposal:

A high-speed camera could, in combination with facial recognition and eye-tracking software, be used to determine who is looking at the screen and exactly what part of the screen they are looking at.

Then, the privacy system simply scrambles the contents of your laptop screen as soon as it notices an unauthorized individual looking at your screen (Figure 2). (When you are the only viewer, the eye tracking camera can recognize you and not scramble the screen.)

 

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Fig. 2: With the camera-based privacy filtering system, the laptop instantly scrambles the screen as soon as it detects that someone besides the laptop owner is looking at the screen. Note that the contents of the laptop look similar at a glance, but are actually scrambled nonsense. This prevents passers-by from immediately realizing that a software privacy filter has been applied (and potentially attracting unwanted attention).

In an extra-fancy system, the scrambling mode could be operational at all times, with the laptop only unscrambling the very specific part of the screen that the user is looking at (Figure 3). This is similar to the idea of foveated rendering, where additional computational resources are directed toward the part of the screen that the user is actually looking at.

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Fig. 3: It might be possible to selectively unscramble only the part of the screen that the user is actively looking at. The region in the user’s peripheral vision would remain scrambled.

Conclusion:

If you own a laptop manufacturing company and are looking for an endless hardware task to employ your cousin or something, this would be a great project!

PROS: The laws of physics do not prevent this from working!

CONS: Might be impossible to use a laptop in a coffeeshop with this system activated.

Stop getting hit by self-driving cars with this one fashion trick that involves putting weird labels on all your clothing! Don’t be the last one to catch on to this new fashion trend.

Background:

In a hypothetical future where self-driving cars are increasingly common, they’ll have to do a really good job of automatically distinguishing between things that require sudden braking (e.g. a person in the roadway) and things that are OK to hit (e.g. a tumbling empty cardboard box).

The issue:

This is a hard problem. When a car gets data from its various cameras (and other sensors), it needs to figure out what exactly it is that it is seeing (Figure 1).

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Fig. 1: This is probably a pedestrian in the roadway, but could it also be a billboard advertisement hundreds of feet away?

Although the specific “distant-billboard-or-close-pedestrian” question in Figure 1 can be answered just by using two cameras to estimate distance, there are situations where the problem must be resolved in a more complex fashion (Figure 2).

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Fig. 2: Top: the image is interpreted correctly, and the car does NOT hit the pedestrian. Bottom: the car incorrectly believes that it sees a sunflower, and collides with it at full speed. Lest you think this is totally implausible, check out some specially-crafted adversarial examples (that can turn a panda into a banana) and a method of tricking lane-following algorithms into swerving the car into oncoming traffic.

Proposal:

We propose to place special “this is a human” symbols on articles of clothing that a human might wear (Figure 3).

When a car sees one of these unusual QR-code-like symbols, it will instantly say “ah, sunflowers do not wear specially-marked shoes, time to hit the brakes!”

To avoid this becoming a fashion disaster, these markings would not be apparently at normal human-visible wavelengths of light, but would only be detectable by special camera equipment.

Perhaps the markings could have fluorescent ink in them, and all cars could drive around with UV lights in the front.

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Fig. 3: Left: this is what the shoe looks like to a human—the markings are invisible to the naked eye. Middle: the camera can see wavelengths of light beyond human ability, and can detect these special markings (shown here as yellow checkerboards). Right: the camera sees the checkerboard, and the object-classification algorithm realizes that this shoe is likely to be attached to a human.

One common objection to many self-driving-car-related issues is “couldn’t some criminal put these markers all over the city, to trick self-driving cars?”

The answer is yes, but it would be as equally illegal as it currently is to put mannequins on a winding road (which would also confuse human drivers).

Conclusion:

This might be redundant with an infrared camera—in most locations, a human already is obviously distinguished from the background environment just by their warm-blooded glow in the infrared spectrum.

PROS: This will definitely make me a ton of money when it is licensed by major car manufacturers. Also, would someone please apply for and pay for a patent on my behalf? Thanks!

CONS: If one of these specially-marked shoes falls onto the roadway (perhaps by falling out of someone’s messenger bag while they’re biking), do we really want every car to come to a screeching halt at the sight of a single unattached shoe?

 

 

Improve the odds of finding a lost pet with this over-engineered license-plate-based system! The ultimate computer vision project for a machine learning startup.

Background:

“Lost cat” and “lost dog” signs are often placed up on telephone poles (Fig. 1), but it’s unlikely that a specific person who sees a lost pet will also have seen the sign (or even know that the pet is actually lost in the first place).

 

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Fig. 1: A person who sees this sign will know to be on the lookout for a lost snake, but the chances of seeing both the snake AND the poster are quite low.

Proposal:

In order to add more people to the lost-pet-searching process, the proposed system is as follows:

On the searchers side:

  • Car owners can add a camera to their car (see license plate example in Figure 2) that constantly scans for unidentified animals. This requires no effort on the part of the driver.
  • The camera saves snapshots and GPS coordinates for every animal it sees, and uploads these to a “Find a Lost Pet” web site. Many of these animals are probably not lost, or even pets!

On the pet-recoverers side:

  • Anyone with a lost pet can post the details of their lost animal and a reward to the “Find a Lost Pet” site. Ideal information would include a photo, approximate location, and the owner’s contact information.

Once the “Find a Lost Pet” image analysis system detects a match between an uploaded image and a lost pet, a “bounty” is issued for the recovery of that pet, and nearby drivers are notified.

Finally, assuming the animal is safely returned in the same number of pieces that it was expected to be in (generally this number is “one”), the bounty is split three ways: the web site, camera owner, and animal-recoverer all get a fraction of the total reward. This aligns everyone’s incentives and encourages people to install pet-scanning cameras in the hope of a payout.

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Fig. 2: This license plate camera is a “dog-scanner” camera that is constantly on the lookout for unidentified potentially-lost animals. Backup cameras like this already exist, so producing the hardware for this system would be relatively straightforward.

PROS: This system will help find lost pets, and definitely won’t be repurposed to create a totalitarian police state.

CONS: Not especially useful in finding burrowed or aquatic animals, so try not to lose one of those.

Become a prey animal by putting eyes on the side of your head. Makes you a safer driver, but also encourages packs of howling wolves to attack you, so beware!

Background:

Human vision is limited to a ~180° horizontal angle (Figure 1) and an even smaller vertical angle.

This means you can easily be blindsided by objects coming from behind you. In ancient times, this was less of a worry, but with electric cars, electric scooters, and bicycles, there are a huge number of fast-moving and potentially-lethal objects that humans must be aware of.

 

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Fig. 1: Normal human vision only uses less than half of the total potentially-available visual information. Many prey animals have nearly 360º vision, so clearly this limitation is not an inherent limitation of biology.

Proposal:

Since cars are now the “apex predator” that is ranked above humans in the food chain, humans should adapt and become prey animals. This requires a visual adaptation to allow for 360º vision, which can be accomplished as shown in Figure 2.

 

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Fig. 2: These “earmuff cameras” feed into the glasses in front, which provide a highly-warped fisheye view of the wearer’s environment. Although binocular vision may be impaired, the benefits of total visual awareness cannot be overstated.

Conclusion:

The example in figure 2 requires complicated electronics, but there’s probably a way to create an optical 360º-vision system that uses no electronics.

A similar product already exists: rear view mirror spy glasses—inexpensive sunglasses with mirrored “wings” that allow you to see behind you.

PROS: May reduce the number of deaths and injuries from accidents caused by a lack of visual situational awareness.

CONS: Can the human visual cortex handle this type of input data? Only one way to find out—experiment on some undergraduates.

Finally, you can become an ant, thanks to the power of VIRTUAL REALITY.

Background:

Currently, there is no easy way to have the experience of becoming a tiny ant [*]. This is a shortcoming that could not be addressed—until now, thanks to modern VR technology!

[*] You could watch the 1989 film Honey I Shrunk the Kids, but that isn’t an interactive experience.

Proposal:

Thanks to virtual reality, you can become an ant in 3 steps:

  1. Get a VR headset.
  2. Create a small remote-controlled car with two cameras on the front.
  3. Set up the R.C. car cameras to transmit to the VR headset.

Figure 1 shows the result of these steps.

Now you can be an ant!

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Fig. 1: Left: someone wearing a VR headset that receives a pair of video signals from the remote-controlled car (orange) shown in the magnifying-glass inset (right)

 

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Fig. 2: The experience of the viewer in VR goggles is shown at right. This is definitely exactly what an ant looks like close-up, as anyone who has seen the “Planet Earth” series can confirm. That’s how you know that this image was drawn with extensive consultation of reference material.

Conclusion:

This “ant VR” system theoretically be used for other purposes as well; maybe the ant-sized drone could check for cracks in hard-to-access parts of bridges or buildings, or an aquatic version could swim through a city’s water system to allow maintenance personnel to both look for leaks AND ALSO pretend to be an eel at the same time. Finally!

PROS: Lets you feel kinship with your insectoid brethren, the ants.

CONS: After spending a while in VR, you might think you actually ARE an ant and become unable to participate in human society.

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Figure 3 (bonus): An extremely detailed technical schematic that will be used for manufacturing.

 

Solve your conference call woes with this one insane tip! Never lean your head weirdly in front of a laptop camera again. FINALLY.

The issue:

During a conference call, it can be difficult to position multiple people in such a way that everyone is actually in-frame.

Usually, either:

  1. Only one person fits into the frame, or:
  2. Everyone is extremely far from the camera, so 95% of the screen area is taken up by a conference table.

Figure 1 illustrates this common scenario.

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Fig. 1: When multiple people are sharing a laptop during a conference call, usually the video looks like the example on right, where only one person is actually fully visible.

Proposal:

An inexpensive prism can fix this problem once and for all (Figure 2). A prism can be placed directly in front of the camera to split the image into multiple horizontally-spaced parts.

Now everyone can participate in the conference call without needing to move the camera around!

conference-call-2-with-prism

Fig. 2: The prism attachment makes it easy to fit everyone into frame. The prism could attach to the camera by means of either a magnetic clip or some sort of suction cup (probably the best solution for laptop screens).

PROS: Encourages conference call participation by people other than whoever happens to be directly in front of the camera.

CONS: Might result in an unflattering “fun house mirror” effect in the final image. (Although this could be fixed in software, or by a more complicated prism setup.)

Revolutionary new “lens-free camera” created in a garage by a crazy inventor—now all your vacation photos will be PERFECT!

Background:

When people go on vacation, 99% of their pictures are of sunsets and monuments that have been photographed thousands of times before.

Sure, that image of a majestic tropical bird perched in front of a waterfall may seem like one-in-a-million shot, but that still means that one hundred variants of it have already been uploaded to Google Photos.

The issue:

It can be a lot of work to frame a shot in an aesthetically-pleasing fashion. But what if we could make use of THE INTERNET to save us the trouble?

Proposal:

Instead of carrying a regular camera, a user can carry a “camera” without a lens or ability to take pictures.

Instead, when the user presses the shutter button:

  1. The “camera” records the user’s GPS coordinates, the time of day, and the current orientation of the camera.
  2. Later, the “camera” syncs this information to the Internet and downloads the most aesthetically-pleasing photo for the specified site and time of day.

So if you were disappointed that you were taking photos of Niagara Falls while it was overcast, no worries: the camera will pick out some majestic waterfall-and-rainbows-on-a-sunny-day photos from online.

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Fig. 1: This “lens free” camera looks like a traditional camera, except it doesn’t actually take pictures—it only records your GPS location and orientation when taking the picture. (The viewfinder shown here could just be a transparent plastic window, not a real LCD screen.)

 

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Fig. 2: Internally, the camera is really just searching for the top-rated image at a given set of coordinate / orientation / time-of-day.

Conclusion:

Stop futzing with shutter speed, exposure, framing, and who knows what else—just let the Internet take your photos for you!

PROS: Saves tons of time! Makes everyone into a master photographer. You won’t have to worry about looking bad in a photo, because you’ll never be in a photo! (Unless you happen to be the subject of the top-rated photo somehow.)

CONS: At least one person will still have to use a real camera to take photos, or else there won’t be anything for the GPS-only camera to find.

 

 

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