Sudheendra Vijayanarasimhan      

I am a third year graduate student in the Department of Computer Sciences at the University of Texas at Austin. I obtained my B.Tech (Bachelor's) in Computer Science and Engineering at the Indian Institute of Technology, Madras.


Currciculum Vitae

Research Interests

I am interested in Machine Learning, Computer Vision, Object Recognition and Categorization. I'm currently working with Prof. Kristen Grauman on actively predicting both the manual effort required to obtain an annotation and the information gain associated with the annotation in image categorization.

Publications

Data

  • Annotation data for MSRC (v1) dataset

  • Here's annotation (object segmentation) and timing data collected on the MSRC version 1 dataset from a large number of anonymous users using the Mechanical Turk interface. This readme file provides details on the data. Also checkout our CVPR 2009 paper for more details. These are some example segmentations that were approved.

    This data was collected with the help of Alex Sorokin who has a general interface for annotating data using Mechanical Turk.

    If you find this data useful for your research please feel free to use it and kindly use the following bibtex entry for citations. BIBTEX

Code

  • Source code used in the Semantice Robot Vision Challenge

  • The Semantic Robot Vision Challenge (SRVC) is a workshop conducted every year where fully autonomous robots receive a text list of objects that they are to find. They use the web to automatically find image examples of those objects in order to learn visual models. These visual models are then used to identify the objects in the robot's cameras.

    I participated in the 2008 event and applied a Multiple-Instance Learning based approach for the problem. Here's the complete source code of our method. This readme file should get you started if you would like to apply our method.

  • Incremental SVM

  • Here's a C++ implementation of the Incremental SVM method of Cauwenberghs and Poggio based on their MATLAB implementation .

Contact

Address:
Department of Computer Science
University of Texas at Austin
1 University Station
CSA 1.106
Austin, TX 78712-0233

Email: svnaras at cs dot utexas dot edu