The state of the art and how we applied it at Finnair. This presentation was held in Futurice Munich Beer & Tech event: Brave new world, AI applied. https://www.meetup.com/Munchen-Beer-Tech-Meetup/events/240575870/
This presentation of about Face Recognition. you can learn about face recognition history, how's it is work traditional and in technical way, introduction of some face recognition software and devices. we don't add any face recognition algorithm in presentation.
The state of the art and how we applied it at Finnair. This presentation was held in Futurice Munich Beer & Tech event: Brave new world, AI applied. https://www.meetup.com/Munchen-Beer-Tech-Meetup/events/240575870/
This presentation of about Face Recognition. you can learn about face recognition history, how's it is work traditional and in technical way, introduction of some face recognition software and devices. we don't add any face recognition algorithm in presentation.
Joy Mountford at BayCHI: Visualizations of Our Collective LivesBayCHI
The lines between art, design, and information are dissolving as we experience new places and objects. Consider, for example, the organic flow of air traffic over North America at daybreak, the bursts of search query memes spreading around the globe, and the pointillist surge of mobile phone usage on New Year's Eve. Using the new techniques of generative data visualization, a new generation of artist/designers/engineer/scientists are creating gorgeous, dynamic experiences driven by massive sets of data about our own lives. Their work comes to life in architectural spaces, on walls of wood and metal and light and shimmering glass clouds suspended overhead. Of course it must be touched to be appreciated and engaged with, simple gestures launch a thousand images and possibilities. Many of these projects have received international recognition. They are primarily 3D applications that can run in real time, but really can only be appreciated by watching them, as movies. These data movies aim to make information easier to understand while being enjoyable to watch. Surprising insights surface through looking at our 'data life' in new ways, and may compel us to design in different, even better ways.
Overview of Computer Vision For Footwear IndustryTanvir Moin
Computer vision is an interdisciplinary field that focuses on enabling computers to interpret and analyze visual data from the world around us. It involves the development of algorithms and techniques that allow machines to understand images and videos, just as humans do.
The main goal of computer vision is to create machines that can "see" and understand the world around them, and then use that information to make decisions or take actions. This can involve tasks such as object recognition, scene reconstruction, facial recognition, and image segmentation.
Computer vision has a wide range of applications in various fields, such as healthcare, entertainment, transportation, robotics, and security. Some examples include medical image analysis, autonomous vehicles, augmented reality, and surveillance systems.
In recent years, the development of deep learning techniques, particularly convolutional neural networks (CNNs), has greatly advanced the field of computer vision, allowing machines to achieve state-of-the-art performance on various visual recognition tasks.
This presentation is part of the webinar. Here is the link for the webinar recording https://www.anymeeting.com/geospatialworld/E955DA81854C39
Presentation Credits: NVIDIA & Geospatial Media
Joy Mountford at BayCHI: Visualizations of Our Collective LivesBayCHI
The lines between art, design, and information are dissolving as we experience new places and objects. Consider, for example, the organic flow of air traffic over North America at daybreak, the bursts of search query memes spreading around the globe, and the pointillist surge of mobile phone usage on New Year's Eve. Using the new techniques of generative data visualization, a new generation of artist/designers/engineer/scientists are creating gorgeous, dynamic experiences driven by massive sets of data about our own lives. Their work comes to life in architectural spaces, on walls of wood and metal and light and shimmering glass clouds suspended overhead. Of course it must be touched to be appreciated and engaged with, simple gestures launch a thousand images and possibilities. Many of these projects have received international recognition. They are primarily 3D applications that can run in real time, but really can only be appreciated by watching them, as movies. These data movies aim to make information easier to understand while being enjoyable to watch. Surprising insights surface through looking at our 'data life' in new ways, and may compel us to design in different, even better ways.
Overview of Computer Vision For Footwear IndustryTanvir Moin
Computer vision is an interdisciplinary field that focuses on enabling computers to interpret and analyze visual data from the world around us. It involves the development of algorithms and techniques that allow machines to understand images and videos, just as humans do.
The main goal of computer vision is to create machines that can "see" and understand the world around them, and then use that information to make decisions or take actions. This can involve tasks such as object recognition, scene reconstruction, facial recognition, and image segmentation.
Computer vision has a wide range of applications in various fields, such as healthcare, entertainment, transportation, robotics, and security. Some examples include medical image analysis, autonomous vehicles, augmented reality, and surveillance systems.
In recent years, the development of deep learning techniques, particularly convolutional neural networks (CNNs), has greatly advanced the field of computer vision, allowing machines to achieve state-of-the-art performance on various visual recognition tasks.
This presentation is part of the webinar. Here is the link for the webinar recording https://www.anymeeting.com/geospatialworld/E955DA81854C39
Presentation Credits: NVIDIA & Geospatial Media
4. ● 1960’s- First system required somebody to locate features on photographs
and calculate distances and ratios to compare to reference data
● 1970’s- 21 specific subjective markers such as hair color and lip thickness
were used to automate the recognition
● 1988- Applied principal component analysis, a standard linear algebra
technique, so measurements didn’t have to be manually computed
● 1991- Discovered that residual error could be used to detect faces in images,
a discovery that enabled reliable real-time automated facial recognition
systems
● 2001- Facial recognition caught media and public’s eye during 2001 Super
Bowl
● Major Players include: NEC Corporation, FaceFirst, Anviz Global Inc, and
Smartmatic
5. ● Images input through a digital video camera
● System analyzes characteristics of a
persons face
● Measures the overall facial structure,
including distances between eyes, nose,
mouth, and jaw edges
● Measurements then retained in a database
and then used as a comparison
● Each human face has approximately 80
nodal points that are detected
8. • 2001 Super Bowl XXXV
• Tampa, FL Police Force supplied with free software
• Identified a handful of criminals, but no arrests were made
• 70,000+ fans scanned without
consent
• Places where this technology
could be helpful:
• Airports
• Casinos
• Retail Stores
• Office Buildings
9. Who would be against an implementation of
facial recognition security measures? Is
this system unfair?
10. ● FaceDeep as accurate as the human
brain
● 97.25% accuracy (humans roughly
97.53%)
● 9 layers of “neurons” able to make 120
million connections in their database
● Better at identifying faces that FBI’s
NGI (Next Generation Identification)
11. ● This app allows access to wide
variety of information simply by
looking at someone
● A person’s name, photos, and
dating website profiles
● Takes pictures and analyzes
pictures in a matter of seconds
12. Would you use this technology? If yes, how
would you use it? If no, does this
possibility make you uncomfortable?
Do you think any of your current
relationships would be different had you
had this technology?
13. • Retail
• Shoplifters
• VIP Customers
• Hotel and Hospitality
Most high-profile customers are "quite happy to have
their information available because they want a
quicker service, a better-tailored service, or a more
personally tailored service“ (New York Times).
14. Would you sign consent
for facial recognition
use in retail and
hotel/hospitality? If
not, what would need
to change?
Do the pro’s outweigh
the con’s?
15. • There are currently no U.S. laws limiting government
agencies or private companies from using facial recognition
• National Telecommunications and Information
Administration
• Similar to DNA sequencing
• Right to control access to and use of biometric data
• Balance between privacy and law enforcement
“Commercial facial recognition technology has the potential to provide important
benefits and to support a new wave of technological innovation,” says John
Verdi, the agency’s director of privacy initiatives, “but it also poses consumer
privacy challenges.”