Brief History of Computer Vision

Source: Google

As any other technology the world has ever witnessed, Computer Vision did not come to us as a revelation just over night. What we see or know about Computer Vision and it's related fields are results of several years of  research and hard work. The first such works started in the 1960s. By then, light capturing digital hardware has already been invented paving the way for scientists and engineers to tackle the challenge of Computer Vision.

1964

Defense contractors Woody Bledsoe, Helen Chan Wolf and Charles Bison launch a facial recognition system for an unnamed intelligence agency. Further developments and iterations went on to change how governments and security bodies such as police match and identify citizens and also suspects from ID photographs stored in their national databases.

1966

Minsky assigns computer vision as an undergrad summer project. The first attempt to solve this problem was made by Seymour Paper. Though this attempt was not as successful as intended, this got scientists and engineers talking.

1970's

This decade saw some progress on interpreting selected images. One advancement was UK Police inventing a license-plate recognition system in 1976 which was deployed around London in 1993 to counteract the threat of IRA bombings.

1980's

Researches attempt using Artificial Neural Networks in Computer Vision to allow for better image recognition but however they quickly abandoned the study as it deemed too difficult with the limited resources of the time. There was a shift toward geometry and mathematica rigor. This decade saw one of the very first beginnings of Vehicle Autonomy using Computer Vision developed by Lockheed Martin, Carnegie Mellon and others. It is a land vehicle that uses video based imaging to follow a road at just 3 mph.

1990's

This decade can be said as the actual birth of Computer Vision that saw the return of Artificial Neural Networks in Computer Vision research under the name, Convolutional Neural Networks and were able to solve a challenging for the time problem, that is digit recognition for bank cheques. It also saw further advancements in Facial Recognition and statistical analysis in vogue.

2000's

Source: Google Images

Reached new heights in object recognition due to the availability of large annotated datasets and video processing began. In 2004, Mars rovers Spirit and Opportunity uses Computer Vision to land successfully in Mars. The first 3D pizza system called called the "Scorpion" builds a 3D profile of 7,200 products per hour using multiple cameras.

2010's

Source: Google Images

Computer Vision began to be deployed in a number of web applications and mobile apps and saw these technologies reach a wider user base. Microsoft Releases Kinect in 2010, a motion sensing camera that can track 20 human features at 30 times per second. Google starts testing it's autonomous cars which uses cameras, LIDAR and artificial intelligence to navigate unassisted in 2012. In 2014, smartphone processors become powerful enough for pattern recognition. Many mobile photography applications could automatically enhance photos and suggest best taken photos from a session of photo shoot.

Today, computer vision is rapidly being utilised in almost every field from, social to health applications, entertainment industry and also military drones and further research is being made in the field. What we are witnessing is the Golden Age of Computer Vision.

References:
https://tordivelblog.com/2014/06/23/scorpion-3d-pizza-sorter-57-years-of-machine-vision-history/
https://cs.brown.edu/courses/cs143/lectures/01.pdf
http://www.egavves.com/category/home/#sthash.PtZp3lvq.dpbs
http://www.consciousentities.com/minsky.htm

Artificial intelligence (AI)

Source: Google Images    

(AI) is the intelligence exhibited by machines or software. Computer Vision mostly is associated with or part of artificial intelligence. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behaviour. (Wikipedia) 

It can also be defined as the  science and engineering of making intelligent machines, specifically intelligent computer programs. It's  similar to using computers to understand the human intelligence. However, AI does not have to confine itself to methods that can be observed biologically.

                                                   Source: Google Images      

Can We Predict The Future of AI?  

Raymond Kurzweil, A very well know American author, inventor and futurist has made many future predictions regarding Technology, The Internet and their explosive growth and how it is going to impact our lives. 

In  The Age of Intelligent Machines, is one of his books that was published in the early 90's Where he predicted that the Internet would have a marvellous impact   in the number of users as well as the content, It grants the users access "to international networks of libraries, data bases, and information services. 

Kurzweil correctly foresaw that the preferred mode of Internet access would inevitably be through wireless systems, and he was also correct to estimate that the latter would become practical for widespread use in the early 21st century. 

He also  extrapolated the performance of chess software to predict that computers would beat the best human players "by the year 2000"  In May 1997 chess World Champion Garry Kasparov  was defeated by IBM's Deep Blue computer in a well-publicized chess tournament.

                                             

                                                                                                                   Source: Google Images

                                     Humans Vs Technology                                 

One of the predictions that made many people afraid of the future, Is that by the year 2030 a robot can be smarter than all mankind combined. Technology has already replaced mankind in many industrial fields which lead to a huge decrease in the global labour force. (after all they won't need to pay the robot a salary). If robots will think on our behalf one day, That can only mean that the human intelligence would be decreasing. 

We used to wash our clothes by hands and then replaced it with washing machines. we also used Calculators as a replacement of our brains to compute simple maths. As well as machines that replaced the labour force, And many more example that we can see in our daily life.

I can only hope that the Artificial intelligence is going to help make the world a better place. And work on the service of humanity. We can't be civilized if everything is improving and humans are doing the opposite.



                                                                                                   Source: Google Images 

      

References: 
https://en.wikipedia.org/wiki/Artificial_intelligence

https://en.wikipedia.org/wiki/Predictions_made_by_Ray_Kurzweil

http://www-formal.stanford.edu/jmc/whatisai/node1.html


                

SNAPCHAT: An Application That Uses Computer Vision

Image: techcrunch.com

Snapchat is a young app startup that has quickly taken over the world of social media. Their very recent update brought a feature called Snapchat Lenses: a feature that can detect and map your facial features and apply live animations on top of it as well as warp your face. This has given the world something completely reckless and share with their friends and family. Some videos made using these lenses has gone viral across other social websites and even on TV channels.

The face recognition technology underlying in this new feature was first created by an iOS app called B2C by Looksery in 2014. Snapchat found the potential of integrating such a technology in their app which has already seen wide adoption all around the world. For Looksery this was the perfect opportunity to bring their face recognition and modification technology to the mainstream.

According to theodysseyonline.com, Looksery focused on creating a program that could alter and transform the look on user's face in real time. They made it with special computer vision programming that could track the movement of users facial expressions and the shape of a user's head. This allowed the users to move their head and have the filter move along with it. It is also possible to recognise two faces and swap each others faces.

Now, this high technology is owned and improved by Snapchat which acquired Looksery for a whopping $150 million, according to Business Insider.

To use Lenses in Snapchat follow the steps below:

1. Go to the Camera screen in Snapchat.
2. Press and hold on a face! Lens options will appear below.
3. Swipe left to select the Lens you want to use.
4. Follow any action prompts that appear, like ‘Raise Your Eyebrows.’
5. Tap the capture button to take a Snap, or press and hold on the capture button to record a video.

Social media apps and websites like Snapchat and Facebook are at the forefront of mass deployment of some areas of Computer Vision technology to mainstream public all over the world. This gives us a solid insight into how our future would look like in years to come given the advancement of such technologies as Computer Vision and it's Facial recognition sub technology.

References:

http://techcrunch.com/2015/09/15/snapchat-looksery/

https://support.snapchat.com/en-US/ca/lenses

http://www.pocket-lint.com/news/135912-snapchat-lenses-how-do-they-work-and-do-they-cost-anything

http://theodysseyonline.com/college-for-creative-studies/people-behind-snapchats-selfie-lenses/395547

What is Computer Vision?

Source: Google Images

Wikipedia defines it as this, "Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions."

Computer Vision can also be thought of as mimicking human vision sensing and vision processing capabilities in Computers or Robotic applications. Sometimes this may be a crucial component of an Artificial Intelligence.

Applications of Computer Vision:

• Face Recognition

• Object Recognition

• Autonomous Vehicles

• Image Search

• Optical Character Recognition

• Robotics

• Remote Sensing

• Augmented Reality

• Automatic Target Recognition 

Listed above are some of the few examples of applications of Computer Vision. As this is a field of computer science in it's infancy, the possibilities of it's applications may be vast and nonetheless, it will be a major part of the upcoming future of intelligent machines.