INDIAN FACE DATABASE

This database contains human face images captured in February, 2002 in the campus of Indian Institute of Technology Kanpur.

This database contains images of 40 distinct subjects with eleven different poses for each individual. When available, a few additional images are also included for some individuals. All the images have a bright homogeneous background and the subjects are in an upright, frontal position. For each individual, we have included the following pose for the face : looking front, looking left, looking right, looking up, looking up towards left, looking up towards right, looking down. In addition to the variation in pose, images with four emotions - neutral, smile, laughter, sad/disgust - are also included for every individual. As an example, images corresponding to one individual are shown below.

The files are in JPEG format. The size of each image is 640x480 pixels, with 256 grey levels per pixel. The images are organized in two main directories - males and females. In each of these directories, there are sub-directories with names as numbers, where each index corresponding to an individual. In each of these directories, there are eleven different images of that subject, which have names of the form n.jpg, where n is the image number for that subject.

Indian Face database is available here.

• This database is not available for commercial purposes. This is made available to help various people in their research.
  
  
• Please cite the use of this database as:
  Vidit Jain, Amitabha Mukherjee. The Indian Face Database. http://vis-www.cs.umass.edu/~vidit/IndianFaceDatabase/ , 2002.
  The bibtex entry is:
  @misc{JainMukherjeeIndianFaceDB,
  author = "Vidit Jain and Amitabha Mukherjee",
  year = "2002",
  title = "The Indian Face Database",
  url = "http://vis-www.cs.umass..edu/$\sim$vidit/{I}ndian{F}ace{D}atabase/",
  }
  
• Please notify us if you intend to use this database.

List of the current users of this database.

• Shoyaib et al. A Reliable Skin Detection Using Dempster-Shafer Theory of EvidenceICCSA 2009
• S.Popley and A. Sanchez. Integration of Texture and Shape Algorithms with Face Recognition using Eigenvectors.
• Karande et al. Independent Component Analysis of Edge Information for Face Recognition. IJIP
• Deboeverie et al. Parabola-based Face Recognition and Tracking.
• Deboeverie et al. Face Recognition Using Parabola Edge Map .
• Wijaya et al. Face Recognition Based on Dominant Frequency Features and Multiresolution Metric.
• Sundaraj. Investigation of facial artifacts on face biometrics using eigenface based single and multiple neural networks.
• A. Khashman. Intelligent Face Recognition.
• Hwang et al. Person Identification System for Future Digital TV with Intelligence.
• Hwang et al. Real-time Person Identification System for Intelligent Digital TV.
• Huang et al. Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments.
• L. Shamir, Evaluation of Face Datasets as Tools for Assessing the Performance of Face Recognition Methods. IJCV 2008
• Hourani et al.SemFace: a human face search engine based on the semantic web.
• Hourani et al. The Human Face Semantic Web.
• Zhu et al. Generalized PCA algorithm for feature extraction. CEA 2008
• C. lu. Face Feature Locating using Adaptive Active Shape Model.
• Karande et al.Face Recognition under Variation of Pose and Illumination using Independent Component Analysis.
• V. Conitzer.Using a Memory Test to Limit a User to One Account.
• K. Uchimura, Z. Hu. Face Recognition Based on Dominant Frequency Features and Multiresolution Metric.
• Neerja, E. Walia. Face Recognition Using Improved Fast PCA Algorithm.
• M. Holia, V. Thumar. Application of PCA in Face Recognition and Performance of PCA based FRS System
• G. Gautam. Recognition and Interpretation of Face Images in Video Sequences Using Active Appearance Models.
• A. Kothari, A. Keskar. Rough Neuro Hybrid Approach Based Pattern Classification. Visvesvaraya National Institute of Technology, Nagpur, India
• L. Jasmine, Race and Age Group - Factors in Friendship. National University of Singapore, Singapore.
• S. Kuznetsov, Carnegie Mellon University, USA
• K. Cameron, Johns Hopkins University, USA
• R. Sahgal, OGI School of Science and Engg., Oregon, USA
• K. Dhou, University of Northern British Columbia, Canada
• N. Hudson, De Montfort University, Leicester UK
• H. Sahota, De Montfort University, Leicester UK
• Chee MWL, Duke-NUS Graduate Medical School, Singapore
• G. P. S. Wijaya, Kumamoto University, Japan
• A. Tomita, Osaka University, Japan
• S. Bentin, Hebrew University, Israel
• D. Ozkan, Bilkent University, Turkey
• Y. Chen, Jinan University, China
• A. Sura, Technical University of Cluj-Napoca, Romania
• Lee L K, Pusan National University, Korea
• B. Dongaonkar, Allahabad University, India
• M. Hajiarbabi, Isfahan University of Technology
• V. Gomathi, NEC Kovilpatti, India
• A. Datar, RGS Technical University, India
• S. Jain, Indian Institute of Technology Kanpur, India
• M. I. A. Attari, Univerity of Engineering and Technology Taxila, Pakistan
• B. Dharini, ??, ??
• F. S. Canales, Universidad de Costa Rica
• A.M.T.B. Adhikari, University of Ruhuna, Galle, Sri Lanka.
• C. Nehal, Sardar Vallabhbhai Patel Institute of Technology, India

For comments, suggestions and further information please contact us.