Tejas Indulal Dhamecha - IIIT

Tejas Indulal Dhamecha
Contact
Information
Research
Interests
IIIT - Delhi, Contact No: +91-9015709368
2 nd Floor, A - wing, Fax: +91-11-2509 9176
Okhla Industrial Estate, Phase III,
E-mail: tejasd@iiitd.ac.in
(Near Govind Puri Metro Station)
New Delhi, India - 110020
Discriminant Analysis, Gender Classification, Face Recognition, Beyond-visible Imaging, Image Acquisition
Systems
Education Ph.D. Candidate (July 2010 - Present) 9.625
Indraprastha Institute of Information Technology-Delhi, New Delhi India
• Advisors: Dr.Richa Singh, Dr.Mayank Vatsa
• Graduate Courses Taken:
Course Grade Course Grade
Image Analysis A Computer Vision A
Advanced Biometrics A Information Retrival B
Probability and Statistics A- Manifold Learning A
Machine Learning A Pattern Recognition A
Bachelor of Engineering (Computer Engineering) (June 2010) 76.04%
Atmiya Institute of Technology & Science, Rajkot, Gujarat, India
Higher Secondary (March 2006) 88.33%
Shree Lal Bahadur Shastri Vidyalaya, Rajkot, Gujarat, India
Secondary (March 2004) 92.00%
Shree Lal Bahadur Shastri Vidyalaya, Rajkot, Gujarat, India
Competitive
Exams
Honors and
Awards
Internships
Graduate Aptitude Test in Engineering
Percentile 96.85 Marks Scored/Total 520/1000
Year of Passing 2010 Branch CSE
Received IEEE Signal Processing Society Travel Grant for attending ICIP-2012.
TCS (Tata Consultancy Services) Research Scholarship in August, 2011 - July 2015.
Secured first rank in Saurashtra University in the first year of B.E., June 2007
Young Scientist Award by Community Science Center - Rajkot, 2001.
The Hong Kong Polytechnic University, Hong Kong
Research Exchange Student 28 th June 2011 - 26 th August 2011
Working as a research student under Dr.Ajay Kumar at the Department of Computing, on the
problem of Near-Infrared to Visible Light face matching.
Academic
Experience
Indraprastha Institute of Information Technology-Delhi, New Delhi India

Teaching Assistant
Duties included conducting tutorials, office hours and leading weekly computer lab exercises. Shared
responsibility for grading exam papers and homework assignments.
• Pattern Recognition, Winter 2012
• Probability and Statistics, Summer 2011
• Computer Organization, Winter 2011
• Digital Circuits, Summer 2010
Professional
Experience
Spadeworx Software Services, Pune, Maharashtra India
Final semester industrial training January 2010 - April 2010
Created a prototype of a health-care editorial suite, which modeled the processes followed in medical
field.
Computer Skills • Computer Vision Packages/tools: emguCV, openCV
• Languages: C# , C , shell scripts, Matlab, XAML, Visual Basic
• Applications: L A TEX, spreadsheet, presentation software, some use of image processing softwares
(mogrify, GIMP), machine leaning softwares (WEKA), IDEs for developing electronic systems
(AVR studio, XILINX)
• Operating Systems: Linux, Windows, Mac
• Hardware Interfaces: Embedded C, some use of Verilog, AtMega8 Controller, Stepper Motors,
Basys2 FPGA board
Publications
Projects
1. Lamba H., Dhamecha, T. I., Vatsa, M. & Singh, R., Incremental Subclass Discriminant
Analysis: A Case Study in Face Recognition, International Conference on Image Processing,
2012. To appear.
2. LambaH., Dhamecha, T. I., Vatsa,M.&Singh, R., IncrementalSubclassDiscriminantAnalysis:
A Case Study in Face Recognition, Technical Report IIITD-TR-2012-006, Indraprastha
Institute of Information Technology - Delhi, March 2012.
3. Dhamecha, T. I., Sankaran, A., Singh, R., & Vatsa, M., Is Gender Classification Across Ethnicity
Feasible using Discriminant Functions, International Joint Conference on Biometrics,
2011.
4. Sankaran, A., Dhamecha, T. I., Vatsa, M., & Singh, R., On Matching Latent to Latent
Fingerprints, International Joint Conference on Biometrics, 2011.
Indraprastha Institute of Information Technology-Delhi, New Delhi India
Incremental Training in Subclass Discriminant Analysis Nov 2011 - Jan 2012
This project aims at coming up with incremental framework for subclass discriminant analysis. We
have been successful in coming up with the framework that can learn new samples in incremental
manner; however we are still working on including new classes in runtime.
Understanding the Effect of Ethnicity in Gender Classification Nov 2011 - NOW
While working on the problem on gender classification previously, it was observed that ethnicity also
plays an important role in it. Goal of this project is to understand “ how ethnicity affects gender
classification and can we come up with ethnicity invariant gender classification”
Cross-spectral Face Recognition
June 2011 - NOW
Theprojectisaboutmatchingtheprobefaceimagestakeninnear-infraredspectrumwith the gallery
containing the face image taken in visible spectrum. We are looking at the problem from the point
of view of heterogeneous face matching. We are still working on this problem.

Discriminant Analysis for Estimating Gender from a Face Image January 2011 - May 2011
The project aims to use discriminant analysis to extract unique features from the face images that
can be used to estimate the gender.
Fusing Near Infrared and Visible Spectrum Face Images to Improve
Face Recognition: A Cross-Spectral Analysis
January 2011 - April 2011
The NIR images are less prone to the illumination noise than VS images. The idea is to fuse these
images, to get image which inherits the good properties of both images. Only the fused images will
be used for the gallery. The bigger goal is to be able to recognize VS as well as NIR face image
provided as query image.
Part-based Face Recognition based on Distinctiveness of the Part August 2010 - December 2010
The idea was to use different parts offace, depending on their distinctiveness, forassociatingidentity
withasubject. Themoredistinct apartis, the moreweightitsdecisionwill haveinthe finaldecision.
Face Recogition using Multiple Classifiers August 2010 - December 2010
Implemented different classifiers like PCA, LBP and LDA to perform face recognition.
Atmiya Institute of Technology & Science, Rajkot, Gujarat India
Camera Projector Interactive System June 2009 - December 2009
It consisted of a software prepared using Java and JMF; and a hardware-which was used as a
Marker. It finds its application for the presentations where LCD projectors are used. As a user
marks a point, using marker, on the projection screen, the camera captures it, and feeds it to
software. The software moves the mouse to the marked position. Moreover if the click gesture is
detected, it behaves accordingly.