Many home security cameras nowadays have facial recognition, which lets you create a database of friends and family members who regularly visit your house. Then, when the camera sees a face, it determines whether or not it's someone in your database of known faces.
The software can be hit-or-miss, based on a variety of factors, from lighting to changing hairstyles, wearing glasses one day but not the next -- and more.
But one thing we know for sure is that this feature is becoming increasingly popular in our devices, not just in home security cameras, but also our phones and as efficiency tools helping to automate airport check-ins. As law enforcement becomes more invested in facial recognition technology, it's already raising serious questions about privacy and civil rights across the board, and bringing calls for governmental regulation.
But let's step back a bit to the consumer realm. Your home is your castle, and the option of having facial recognition devices therein is still a compelling option for those who want to be on the cutting edge of smart home innovation. Let's take a look at the facial recognition cameras we've tested recently, to see which models are the best and to help you determine if one would work for you.
Note that CNET may get a share of revenue from the sale of the products featured on this page.
If we're talking about sheer facial recognition capabilities, the Nest Hello, the Nest Cam IQ Indoor and the Nest Cam IQ Outdoor (all of which are essentially the same camera), win by far. Of those models, the Nest Hello is my top pick for facial recognition because it's the least expensive of the three and has the most opportunity to give you important information about who's at your front door.
Nest's IQ Indoor can tell you who's already inside your house, but the Hello, as well as the IQ Outdoor Cam, tell you who's outside your house. The Hello doorbell's eye-level location has the best chance of monitoring and seeing the most visitors, too (although I suppose you could install the 9 IQ Outdoor cam at eye level if you wanted).
The snag with the Hello and other face-tracking Nest cams is that you do have to pay for the facial recognition feature. That means for facial identification, you have to subscribe to the Nest Aware cloud subscription service. Learn more about Nest Aware.
Still, the Nest Hello is also a pick for best overall video doorbell. So it's a win/win, whether or not you want to enable facial recognition. Read the Nest Hello review.
The Tend Secure Lynx only costs . Given that, I was skeptical that this camera would deliver, but it does. Not only does the camera itself perform well and offer multiple nice features like free seven-day event-based video clip storage, but it also has facial recognition free of charge (unlike the optional Nest Aware service).
Create your database of familiar faces, and the Lynx takes over. There is a bit of a learning curve as it becomes familiar with each face, but it's a very good option if you want an inexpensive indoor home security camera with decent facial recognition. Read the Tend Secure Lynx review.
The 9 Nest Cam IQ Indoor is similar to the Nest Hello doorbell. It has facial recognition (if you sign up for a Nest Aware subscription) and lets you know who walks in front of the camera's field of view with consistent accuracy.
But it also has a number of additional benefits. Because it is an indoor camera, Nest gave it an integrated Google Assistant speaker. That means the camera essentially doubles as a Google Home speaker and can answer basic questions like what the current weather or traffic is in your area -- and control a variety of Google-Assistant-enabled smart home devices. It also works with Amazon Alexa. Read the Nest Cam IQ Indoor review.
Here's a recap of the facial recognition cameras we've installed and tested recently.
Worth considering, but not as good as the top picks above:
Note that the recommendations above were at the time of testing, and could change based on later software updates. We'll periodically update this list as such changes warrant.
When setting up a camera with a facial recognition function, you create profiles of individual people, by either taking their picture in real time and adding it, or using an existing photo that you have of them. From there, The face recognition camera should be able to distinguish human faces from every other type of motion activity and single out the ones it recognizes from your database of familiar faces. When it's working optimally, you will get an alert that says the camera saw "Chris," "Molly" or whoever is in your database.
There are many use cases for this type of functionality, but some common ones include getting an alert when your kids get home from school, or if a dog walker or a family caregiver shows up. It creates peace of mind when you're expecting someone to show up and you want an automated alert telling you they have (especially when you aren't home to greet them).
But it also helps in security scenarios, since the camera is essentially distinguishing between faces it recognizes and those it doesn't. That way, if your camera sends you an alert that it saw someone on your front porch or walking into your house, but you don't recognize them, you can more quickly send the information to police officers in the event of an actual break-in or theft, instead of having to sift through dozens of generic motion alerts to find the activity.
Viewing the facial recognition feature inside the SmartCam app.
The best way to test these cameras is to create a database, which is what I do when I test a camera with facial recognition (see the screenshots above). I add people to my database and let the camera do the rest. It's best to give these cameras at least a few days, because some improve significantly, even over a short period of time, as they see faces at different angles.
Then it's a matter of doing an analysis of how well the camera actually recognized faces. How often did it correctly identify my face versus someone else's face? How did it do when approached at different angles and changes to hairstyles and clothing accessories? Was the camera able to detect faces at all? Some occasionally struggle to detect any faces, even ones that claim to have facial recognition, and instead mark the activity as a basic motion alert (ahem, Tend Secure Lynx Pro).
Amazon's doorbell and security camera company, Ring, filed two patents related to facial recognition in 2018. The patents suggest that future developed Ring products might be able to automatically detect and identify faces from "most wanted" lists or a watch list and automatically send notifications to law enforcement officers. Here's an excerpt from one of the patent filings:
A video may be analyzed by an A/V recording and communication device that recorded the video (and/or by one or more backend servers) to determine whether the video contains a known criminal (e.g., convicted felon, sex offender, person on a "most wanted" list, etc.) or a suspicious person. Some of the present embodiments may automatically submit such video streams to the law enforcement agencies.
"Amazon is dreaming of a dangerous future," ACLU attorney Jacob Snow said in a blog post.
"The history of discriminatory government surveillance makes clear that face surveillance will disproportionately harm people already targeted by the government and subjected to racial profiling and abuse — immigrants, people of color, and the formerly incarcerated," Snow added.
Right now, Ring cameras don't offer facial recognition at all. Models that do, like the Nest Hello, are only designed to identify a person you add to your list of "familiar faces." They won't draw from a law enforcement list to determine if a convicted felon is nearby -- or reach out to law enforcement if they spot a face that could match someone in a database.
While we know of no ethical breaches associated with these cameras on the market right now, the reality is we have no way to verify how the biometric data is used. Even if we give the companies involved the benefit of the doubt regarding their analytics and data usage policies, those policies could change at any time. And when you consider that Ring is owned by Amazon and Nest is owned by Google, the potential for a Big Brother scenario is readily apparent.
We'll continue to keep an eye on home security cameras, doorbells and other devices with built-in facial recognition tech, to follow along with any changes in industry trends -- and to see if any new models come close to matching the smarts of Nest's Hello buzzer.
Originally published last year.B:
【宁】【茹】【重】【新】【从】【家】【里】【翻】【箱】【倒】【柜】，【找】【到】【了】【一】【颗】【融】【化】【的】【有】【些】【不】【像】【样】【的】【糖】【果】。 【不】【过】【好】【在】【有】【外】【壳】【包】【着】，【不】【至】【于】【没】【法】【吃】，【反】【正】【是】【给】【谢】【武】【吃】【的】，【宁】【茹】【觉】【得】，【不】【会】【死】【的】。 【宁】【茹】【只】【是】【稍】【微】【犹】【豫】【了】【一】【下】，【便】【拾】【起】【了】【糖】【果】，【往】【外】【面】【跑】【去】。 “【你】【怎】【么】【才】【来】，【我】【都】【要】【晒】【脱】【皮】【了】。” 【谢】【武】【抱】【怨】【道】。 【但】【语】【气】【却】【带】【着】【一】【丝】【小】【心】。 【其】【实】
【反】【正】【那】【人】【落】【入】【蛇】【窟】，【就】【算】【拉】【上】【来】，【只】【怕】【也】【被】【蛇】【咬】【得】【差】【不】【多】【了】。 【四】【个】【人】【又】【交】【换】【了】【一】【个】【眼】【色】，【然】【后】【便】【走】【过】【去】，【帮】【着】【林】【依】【把】【春】【和】【哑】【姑】【给】【拉】【了】【上】【来】。 【等】【把】【两】【个】【人】【拉】【上】【来】，【哑】【姑】【已】【经】【满】【脸】【发】【黑】，【整】【个】【人】【晕】【了】【过】【去】。 【春】【的】【一】【只】【手】，【也】【是】【乌】【黑】【乌】【黑】【的】，【软】【弱】【无】【力】【的】【垂】【在】【身】【侧】。 【只】【不】【过】，【他】【的】【眼】【睛】【还】【睁】【着】，【只】【是】【有】【气】【无】【力】
【当】【苏】【青】【羽】【睁】【眼】【看】【到】【第】【一】【抹】【光】【亮】【时】，【苏】【青】【羽】【的】【心】【死】【灰】【复】【燃】，【像】【是】【看】【到】【了】【希】【望】。 【入】【眼】【是】【一】【个】【暗】【沉】【沉】【的】【居】【室】，【四】【方】【四】【正】，【每】【一】【个】【角】【上】【都】【挂】【了】【油】【灯】，【用】【来】【照】【明】。 【她】【躺】【着】【的】【地】【方】【是】【一】【张】【床】，【床】【上】【铺】【了】【一】【层】【不】【知】【道】【是】【什】【么】【动】【物】【的】【皮】，【软】【软】【的】，【摸】【上】【去】【很】【舒】【服】。 【床】【靠】【着】【后】【面】【的】【墙】【壁】，【她】【的】【正】【前】【方】【有】【一】【道】【机】【关】【门】，【相】【比】【那】【就】【是】百分百高手论坛香【其】【实】yism【公】【司】【在】【韩】【国】【的】【地】【位】，【虽】【然】【不】【是】【最】【顶】【尖】【的】【那】【一】【层】，【可】【是】【因】【为】【公】【司】【的】【性】【质】【以】【及】【旗】【下】【艺】【人】【的】【争】【气】，【也】【使】【得】sm【公】【司】【在】【面】【对】【顶】【级】【资】【本】【家】【的】【时】【候】【有】【一】【定】【的】【底】【气】，【可】【以】【在】【某】【种】【程】【度】【上】【完】【全】【无】【视】【外】【人】【的】【威】【胁】。 【要】【知】【道】，【这】【在】【韩】【国】【是】【根】【本】【不】【常】【见】【的】【事】【情】，【毕】【竟】【韩】【国】【说】【到】【底】【还】【是】【资】【本】【主】【义】【控】【制】【的】【国】【度】，【只】【要】【有】【钱】，【甚】【至】【都】【可】
【天】【机】【门】，【一】【个】【不】【存】【在】【的】【地】【方】，【准】【确】【来】【说】，【是】【不】【在】【此】【界】【中】。 【准】【确】【来】【说】，【所】【有】【来】【到】【影】【州】【的】【人】，【都】【被】【称】【为】【天】【机】【门】【人】，【所】【谓】【天】【机】【门】【的】【少】【门】【主】，【也】【不】【过】【是】【此】【界】【的】【第】【十】【一】【人】【而】【已】。 【外】【面】【的】【环】【境】【之】【糟】【糕】，【实】【在】【无】【法】【用】【言】【语】【来】【形】【容】。【看】【着】【满】【地】【的】【异】【兽】【骨】【头】，【以】【及】【那】【厚】【厚】【的】【一】【层】【骨】【头】【化】【成】【的】【白】【粉】，【季】【诺】【也】【无】【法】【想】【象】【这】【里】【到】【底】【经】【历】【了】【什】
【那】【七】【八】【道】【青】【色】【的】【剑】【气】【就】【像】【是】【催】【命】【的】【符】【咒】【一】【样】，【封】【锁】【了】【高】【万】【辽】【所】【有】【可】【能】【的】【闪】【避】【空】【间】。 【剑】【气】【这】【种】【东】【西】【之】【所】【以】【被】【武】【林】【尊】【为】【宗】【师】【级】【的】【专】【属】，【就】【是】【因】【为】【它】【拥】【有】【一】【个】【无】【坚】【不】【摧】【的】【属】【性】。【就】【像】【是】【自】【己】【的】【枪】【气】【一】【样】，【戳】【过】【去】，【就】【没】【有】【什】【么】【东】【西】【能】【够】【阻】【挡】，【结】【果】【一】【定】【是】【个】【窟】【窿】！ 【在】【最】【危】【急】【的】【时】【候】，【高】【万】【辽】【锻】【炼】【了】【二】【十】【年】【的】【身】【体】【素】【质】【救】
【凌】【天】【站】【在】【场】【中】【面】【带】【微】【笑】【的】【看】【着】【那】【名】【少】【年】，【他】【对】【着】【少】【年】【轻】【轻】【的】【一】【点】，【一】【道】【强】【大】【的】【灵】【力】【从】【手】【指】【冲】【出】。 【灵】【力】【的】【光】【芒】【照】【耀】【了】【整】【座】【大】【殿】，【无】【数】【人】【合】【上】【了】【双】【眼】。 【无】【可】【匹】【敌】【的】【灵】【力】【落】【在】【少】【年】【的】【身】【上】，【一】【口】【鲜】【血】【从】【他】【的】【嘴】【里】【吐】【出】，【落】【在】【地】【上】。 【他】【目】【光】【震】【惊】【的】【看】【着】【凌】【天】，【双】【手】【捂】【着】【自】【己】【的】【胸】【口】，【瞪】【大】【双】【眼】：“【这】【怎】【么】【可】【能】【呢】？【怎】