I think that we all know about some of the neat software of the Nokia N900 such as Chrome and thatFirmware update a while ago.
At least, that is what these people at the University of Manchester in the UK are working on. Their prototype is able to track up to 22 facial features in realtime with the front facing camera.
As you can see in the video, it has the ability to track when the camera is tilted, or even upside down. This active interface was developed for the EU-funded Mobile Biometrics, or MoBio project.
So, will all phones have this face recognition? That would imply that instead of passwords, you have to just let it scan your face.
When social networks spread like wildfire through college campuses, it arguably wasn’t messaging friends, announcing events, or trading goods that drove the most use. It was browsing and (mostly) innocuous stalking. Humans are intensely social and curious, and technology now lets us learn more about each other faster than ever before.
Pew Research reports a third of U.S. adults and two-thirds of U.S. teenshave social network profiles. Two-thirds of these users publicly post photos or videos of themselves and friends; 20% are even sharing nude or semi-nude photos. Combine that with news, government, and third party sources and you have hundreds of millions of identifying photos. With more than half of us searching about others online, this has positive and scary implications. Either way, these behaviors will only increase.
The ubiquity of mobile cameras, public sharing, and liberal laws on photography enable a new service: facial recognition from mobile phones. Let’s look at what a company like that could do — we’ll call it FaceTrace.
Like a Shazam for people, FaceTrace would be a mobile application that lets users snap a photo of someone, automatically upload it for comparison to a large database of public photos, and learn more about who they are. Face recognition has improved significantly through services like Face.com, which works even for photos in low light and different angles.
Why would people use FaceTrace?
Curiosity: Like Facebook, the main use case probably isn’t utilitarian but personal. Want to know who that hottie is and whether they’re single? Wondering if that vaguely familiar person is a celebrity or someone you know? Looking for some shared trait to subtly bring up in a conversation? FaceTrace could tell you.
Identifying missing people: 2,700 people are reported missing every day, equaling almost a million people annually. Half of them are juveniles. FaceTrace could help identify whether a suspicious or lost person is indeed missing. With training, FaceTrace’s technology could also work for lost pets.
Identifying criminals: If you see someone suspicious or a crime in action, FaceTrace could compare the suspect’s photo to a public database of mugshots, helping you decide whether to alert the police and head for the hills. FaceTrace could work with police departments to run these checks automatically and send the cavalry when needed.
Later versions of FaceTrace may allow users to identify places and inanimate objects. This would be a powerful form of search for traveling, buying, publishing, and discovery.
FaceTrace could be a free service monetized by advertising and premium features, such as seeing additional information beyond name and performing more than a few searches per day. Police departments, banks, convenience stores, casinos, and other organizations with an interest in identifying people would also likely pay for FaceTrace. Many currently have stationary face recognition cameras but could benefit from mobile access (to the chagrin of robbers and card counters everywhere).
FaceTrace would be capturing a large amount of photos, which suggests a viral marketing strategy. Users could choose whether to publicly share this media, which FaceTrace could tag with a “Captured by FaceTrace” caption. Millions of photophilic users already share their photos with friends so these links may spread quickly.
Face recognition for consumers is still fairly new, so there is not much competition. Augmented reality startups like Layar are impressively adding background information to snapped photos, though they have focused on places and not people. Face.com has focused on identifying people through Facebook, not the wider world. Either of these startups might enter this space, but there are enough possible applications for FaceTrace to focus on just one.
A key question is whether FaceTrace would terminally freak people out. The general acceptance of Google Street View, Loopt, Facebook photos, and many other privacy encroaching startups suggests FaceTrace’s appeal would outweigh the appalled. FaceTrace could let people opt-out of identification on the service, just asJigsaw does for its business card sharing network. Even among those who worry about online privacy, Pew Research reports only half do anything about it. Right or wrong, privacy concerns continue to be more amorphous than actionable.
I feel mixed about this trend, but it’s inevitable that the web will link us in ways beyond our control. Like any tool, FaceTrace has the potential for both misuse and good. Hopefully, the first company to do this will bring us willingly together instead of guarded from afar.
Vodafone K.K. announces the introduction of a Face Recognition function that authenticates customers by sensing their facial features to increase mobile phone security. The new function will be included in the Vodafone 904SH, a new 3G handset by Sharp scheduled to go on sale in late April 2006.
The Face Recognition function employs software based on Oki Electric Industry's "FSE (Face Sensing Engine)", embedded facial image processing middleware, and utilises the sub-camera located close to the main display to recognise customers by sensing the position of their eyes, eyebrows, mouth and other facial features. By pre-registering a customer's face and a secret question and answer, the camera will automatically activate when the handset is opened and authenticate a customer in less than a second.
When the Face Recognition function is enabled the keypad will be locked until the handset is opened and the pre-registered customer's facial features matched. Also, if facial features cannot be properly sensed due to dark or backlight conditions, the face and secret question of the person who opens the handset will be displayed and the handset can be unlocked by entering the appropriate answer.
The Face Recognition function helps ensure the security of their handsets by preventing misuse by third parties, and can also protect private information such as registered numbers, mail addresses and mails in the event that their handset is lost or stolen.
In addition, the function also features a Mask Mode, which enables the sensing of facial features even if customers are wearing masks.
Mobile phones could soon be equipped with facial recognition technology, if some biometric sensor software launched by Japanese company Omron this week is commercially successful.
Omron's Okao Vision Face Recognition Sensor software allows PDAs (personal digital assistants), mobile phones or other handheld devices to use a built-in camera to recognize the face of their owner. Checking the authenticity of a person in this way could bring greater security to a device, the company said.
"Mobile devices are carrying ever more personal information including address books, schedules and payment information," said Masato Kawade, senior manager of the Sensing Technology Laboratory in Kyoto, Japan. "As a result, the sensor (software) has been designed to protect this information even when the mobile phone is lost or stolen."
Many have argued that facial recognition systems too often grant access to those who should not have it. But Omron said in a statement that its software gives the correct result more than 99 percent of the time.
Omron said the software is compatible with the Symbian, BREW (Binary Runtime Environment for Wireless), embedded Linux and Itron operating systems. Photos take about a second to register and take up to 450KB of memory.
The Okoa Vision Face Recognition Sensor will be on display at the Security Show 2005 in Tokyo later this week.
Read more: http://news.cnet.com/Mobile-phones-get-facial-recognition/2100-1039_3-5595225.html#ixzz13kTpX7Pg
ASIA : OMRON Corporation has announced “OKAO Vision Face Recognition Sensor”, a world first* in face recognition technology which can be implemented in PDAs, mobile phones or other mobile devices with a camera function.
The ability to recognize and verify the authenticity of the user through face recognition is meant to contribute to greater security and safety for mobile devices, and the information they contain, in the future. The technology will be on show at the “Security Show 2005”, which will be held at Tokyo.
“Functionality in mobile phones and other mobile devices is upgrading significantly from simple phone calls and e-mails to include a variety of access, payment and planning services. As a result, mobile devices are carrying ever more personal information including address books, schedules and payment information,” said Masato Kawade, Senior Manager of the Sensing Technology Laboratory in Kyoto. “The “OKAO Vision Face Recognition Sensor”, featuring OMRON’s “Sensing & Control” core technology, has been designed to protect this information even when the mobile phone is lost or stolen.”
Camera equipped mobile units enabled with the “OKAO Vision Face Recognition Sensor” require no additional hardware. Users register their own face image to their unit with the unit’s camera. To use the unit, the user simply takes his or her own photo. The “OKAO Vision Face Recognition Sensor” will automatically detect the user and unlock the unit. The verification process takes less than a second from snapping the photograph. Further, there is no need to adjust the camera position when taking the photo. If the face is included in the photo, the sensor will detect the owner automatically.
The new sensor is made possible with OMRON’s “OKAO Vision”, a core company sensing technology, which allows the technology to transcend previous limits in memory capacity and processing ability by successfully downsizing and speeding up the algorithm. The sensor tests successfully more than 99 times in 100, and is fully Symbian, BREW, embedded Linux, and ITRON OS compatible.Data registration measures 1.5 KB per photo, while memory usage measures just ROM 450 KB and RAM 370 KB. Full processing time is approximately one second with MSM 6500.
*According to our research on face detection and recognition technology as of February 28th, 2005.
• Features
1. Camera equipped mobile units enabled with the “OKAO Vision Face Recognition Sensor” require no additional hardware.
2. The verification process takes less than a second from snapping the photograph.
3. No need to adjust the camera position when taking the photo. If the face is included in the photo, it will automatically detect the owner’s face.
• Specifications and performance
1. 99% recognition: The sensor verifies the owner 99% or more (OMRON tests).
2. Memory usage: ROM 450 KB, RAM 370 KB
3. Registered data size: 1.5 KB per photo
4. Processing time: approx. one second ( with MSM 6500)
5. Capable OS: Symbian OS, BREW, embedded Linux, ITRON
Well friends, a Catalan company has developed a software protection for mobilephones, which can block device and to unlock through the front chamber will make a scan of theface and if it corresponds with the default in a profile that you have to do before, lets you access. If the lighting is not good (at night, for example) can also unlock by entering a code before you default has to adjust the profile before he commented. I have tried it on the N95 and it works perfectly, 2 files are installed separately and only you create an icon. Start up perfectly, you give to create new profile, you must enter a name, makes you 3 pictures of the face and then intruducir the code to dial in case of low light. You have the option of multiple profiles, and the first to be created is the Administrator and it is impossible to erase (only uninstalling and reinstalling the application). Theapplication is in English but understands perfectly. The only thing missing for me to run (because I already have my profile set up and each time I want to access the application makes me face recognition and all that works right) is to make it work locks and unlocks the keypad that’s not make it though the objective of the implementation is essentially that.
Let’s see if we manage to operate between all that aspect.
Supported Devices
N91 8GB , Nokia 3250 , Nokia 5500 , Nokia 5700 , Nokia 6110 Navigator , Nokia 6120 , Nokia 6121 , Nokia 6290 , Nokia E50 , Nokia E51 , Nokia E60 , Nokia E61 , Nokia E61i , Nokia E62 , Nokia E65 , Nokia E70 , Nokia E90 , Nokia N71 , Nokia N73 , Nokia N75 , Nokia N76, Nokia N77 , Nokia N80 , Nokia N81 , Nokia N81 8GB, Nokia N82 , Nokia N91 , Nokia N92 , Nokia N93 , Nokia N93i , Nokia N95 8GB , Nokia N95
and all of the Series 60 v3 devices !!
A group of people in institutes are designing a fast and efficient face image browsing system on CE (Consumer Electronics) devices. The system uses three methods such as facial region detection and facial feature extraction, facial vector clustering, and DB handling for face meta data.
Given pictures, a facial region detection algorithm is applied to each picture and then Gabor-Wavelet features of interesting points in each detected face are extracted. Next, a facial vector clustering technique makes all the facial features, which corresponds to faces, be clustered in an appropriate manner.
In general, a face recognition technique requires a registration procedure, i.e., a user should register face photos as the base, but the system gathers daily pictures automatically. Finally, the DB is updated in order to browse photos by face specifics in real time. This procedure has been presented by some researchers. They have developed a procedure and algorithm, and an easy and efficient UI for a face image browsing system on consumer electronics devices.
Another problem for such applications on cellular devices is display: how to efficiently present the recognized facial or other images on the small screen of such devices.
Visual information presentations on small displays are increasing as the use of cellular communication is increasing day by day. Digital image is one of the most popular forms of visual information which is easily shared and accessible. However, a challenge is to provide a better user experience on heterogeneous small sized screens. Some researchers developed, a novel and efficient technique to browse images by automatic panning and zooming on region-of-interests (ROIs) of image for small display device users. pictures are classified into two different classes and ROIs of image are extracted by using top-down and bottom-up approaches. ROIs are browsed using different intuitive and study based methods. The proposed system is evaluated by subjective test and evaluation results show that the proposed system is an effective large image displaying technology on small displays.
In the future, we will see more advanced and mature facial recognition and display technologies for mobile deices. And see the applications of these techniques being used in our daily life for a secure and wonderful world.
Dual Sim Mobile
