Mission & Vision

Promote learning and system development in the field of Computer Vision and Biometrics. The research community will be constantly working to exchange ideas and become accustomed to the field through formal interactions with the experts of the domain. The lab will work as a channel to bring project funding from Government and Private sectors, which will facilitate member students, faculty and researchers to work on the real world problems in a collaborative environment.

Research Fields

Machine Learning

Computer Vision


Image Processing

Core Objectives

  1. The Lab will provide a platform to the students, faculty and research fellows to work together and initiate teaching and research activities in the area to unveil various concepts, and tools.
  2. The center will provide a common ground to the research community to discover challenges and possible solutions in computer vision.
  3. Teaching and learning will be the backbone of the future research activities, which would involve all stake holders.

The proposed center will contribute:
  1. In enhancing of quality education provided by Institute with emphasis on domain specific expertise.
  2. Grooming and Nurturing young talent willing to work in the field and facilitate with ample opportunities and guidance.
  3. In promoting research through investigating existing problems that can be solved with available tools and applications. 
  4. In identification of the problems where computer vision, machine learning and biometrics could serve as one of the best possible solutions 

The proposed Lab having the capability to:
  1. Establish infrastructure mostly through research funding.
  2. Leverage campus and state collaborations to that each benefits the other
  3. Provide seamless support between and among student service areas (including advising, tutoring, counseling, etc.),
  4. Productively involving both staff and faculty in these areas
  5. Expand into new, and emerging technologies
  6. Education, assessment, undergraduate research, etc.
  7. Collaborate with faculty, staff, students, community members, and programs engaged in related forms of experiential,
  8. Community-based teaching, learning, and scholarship, thereby helping to strengthen such efforts and generating new models.

Recent Events

  • October 29-30, 2017

    Cognition and Biometrics

    Biometrics for Humanity, Cognitive Biometrics, Multimodel Biometrics, Machine Learning for Biometrics, Python and Deep Learning Libraries (Tensorflow), Face Recognition using Deep Neural Network, Image Captioning using Deep Learning, Multimodel biometric recognition using Deep Architecture

  • December 24, 2017 - January 5, 2018

    Graphical Models for Machine Learning

    Graphical models provide a powerful framework for machine learning that allows effective representation of dependency between disparate factors and enables the use of principled probabilistic methods for inference and parameter estimation. This course provides an introduction to graphical models. The course will also feature a set of hands on computational assignments that will help students develop deeper familiarity with the models.

  • January 4, 2018

    Publication Etiquette and Ethics

    Publishing a research paper is usually an exciting experience for most researchers. In this excitement, it is important to not forget that the writing process for the first few manuscripts also often lays the ground for future habits. This presentation, intended for authors unfamiliar with the process of publishing a technical paper, provides a guide to established etiquette and ethics in scholarly publishing.

  • Be Part
    Of Our


5322, Third Floor, Computer Center (CC-3)

Indian Institute of Information Technology - Allahabad

Devghat, Jhalwa, Allahabad-211015, Uttar Pradesh, INDIA