How to begin your career in Computer Vision and Machine Learning Field?

This post is for Computer vision enthusiasts. We are highlighting the focal point of resources and computer vision tutorials for all CV aficionados and get themselves started in this emerging field. As a passionate beginner in the field of computer vision, we hope you find this useful.
Some prior knowledge about linear algebra, calculus, probability and statistics would definitely be a plus but its not always required. The most important thing is to get started and you can learn other essential things on the fly.
Courses:
  • Computer Vision – Mubarak Shah (UCF) : All the materials related to the course are available online and what is more interesting is that even the video lectures are available.
  • Computer Vision – Subhransu Maji (UMass Amherst) : Provides access to all the lecture materials and assignments but there are no video lectures.
  • Visual Recognition – Kristen Grauman (UT Austin) : This Provides links to some of the interesting and fundamental papers in computer vision.
  • Language and Vision – Tamara Berg (UNC Chapel Hill) : This course is basically aimed towards exploring topics straddling the boundary between Natural Language Processing and Computer Vision.
  • Convolutional Neural Networks for Visual Recognition – Fei-Fei Li and Andrej Karpathy (Stanford University) : This course is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for computer vision tasks with a main focus on image classification.
Some additional resources:

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Computer Vision
In addition to this, it is very useful to be aware of most of the basic image processing techniques presented in this book Digital Image Processing – Gonzalez 2007
OpenCV Programming
Software Packages:
You can find an exhaustive list of links presenting code which implements some of the standard vision algorithms at http://www.cvpapers.com/rr.html
Major Conferences: 
Below are some of the major conferences listed in their ranking order.
Most of the papers published in the above mentioned conferences can be accessed at http://www.cvpapers.com/index.html
Nice way to keep track of the conferences deadline is via http://conferences.visionbib.com/Iris-Conferences.html
Now that you have acquired some knowledge of computer vision and Deep Learning (from the previous post), please feel free to compete in Kaggle competitions (best way to put your learning into practice).
If you would like to have any guidance/support in CV domain or have any additional resource information, we would love to hear it without judging you. You may drop your comments below.

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Facial Recognition For On-the-field and In-the-office Employees

facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database.

It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems.

There are numerous biometric security systems in the world. These biometric systems are well adopted and  have proven their utility in multiple scenarios and conditions. Although, no technology is cent percent right but delivering a trust worthy and reliable solution for various use cases has always been a great challenge accepted by the technologist , researchers and entrepreneurs across the world.  Facial recognition system is one of the unique way of biometric identity verification since ages. This system includes many variations like access control system, visitor management system, time attendance system and many more. These applications enhance the security level to many premises such as schools, offices, government buildings, educational institutes, and other organizations. It is not only beneficial for security purposes, but also for controlling human resources by ensuring their presence at right time and location.

The Visual Identification & Tracking Systems (MVITS) is a novel and creative way to track and monitor your on-field and in-office employees/staff. MVITS is a unified solution which ensures both the on field force employees presence at right time and location and simultaneously ensuring the check in  check out time of the in-the-office employees.

Currently the visual identification system is based on the patent pending technology of facial recognition which widely used to record several factors like on-field & in-office presence and absence,location details of the meetings, overtime and under time, authorized and unauthorized leaves, etc. of each employees and staff of the company. This system includes several steps which enables its tracking work. The first step involves the employees to enroll themselves by using their mobile/desktop/laptop devices which has built in web cam . Based on the concept of BYOD– Bring Your Own Device, it captures the facial features of individual employee and uploads to the cloud to build the database. This process of building the database is OTP- One Time Process called “enrolment”.  Next time when the employee/staff  use the application,  it automatically detects and recognises the employee to ensure his/her presence at the right time and location.

Still many small and medium companies are using the pen-paper and log book based attendance system. This is highly time-consuming and effort driven process. This traditional way of ensuring the productivity has always  been prone to problems like data manipulations, proxies, data loss, data mismanagement , lack of analytical information and many more.