I am currently working at an awesome new startup, Magic Leap, developing an augmented reality product.
I previously worked as a research scientist in Amazon and Intelligent Automation, Inc.
From 2007 to 2011, I was a post-doc/visting researcher at the Institute for Advanced Computer Studies (UMIACS), University of
Maryland, College Park, working with Prof. Yiannis Aloimonos
on active vision and robotics. I obtained my Doctorate degree from National
University of Singapore (NUS), Singapore in Feb 2011.
Prior to this, I worked in STMicroelectronics as a design engineer for two years after completing my B.Tech degree from IIT Kanpur (India) in 2003.
My email address is [last_name]email@example.com. In case you are wondering, my last name is "mishra".
My small but useful robot is in the picture on the right which you can click to find more about it.
My ultimate research goal is to develop a robust vision framework, using intuitions and insights drawn from our understanding of how the Human Visual System (HVS) works. The most significant step towards that goal that I have taken so far is to incorporate fixation into visual processing. The inspiration for this came from a rather simple observation that even when our eyes continuously fixate at different things in the scene to see/preceive them, most computer vision algorithms are yet to give any significance to fixation. We believe that fixation (a part of visual attention) is the reason why human visual system works so well. In fact, I have put together a small Psychophysical experiment for you to check it out yourself how critical a fixation can be for visual perception.
In our ICCV 2009 paper, we have already shown how segmenting a fixated object (or region), instead of segmenting entire scene all at once, is an easier and better defined problem. A point is given inside the object of interest, and the algorithm extracts the "optimal" closed contour around that point. This closed contour is the boundary of the object. To segment multiple objects, we simply have to fixate inside all of the objects and carry out the segmentation process for each fixation.
Now to fixate inside objects automatically, we have used another important characteristic of the HVS which is the concept of border ownership. Essentially, the cells in our visual cortex not only detect edges but also record a pointer to the object side of the boundary edges. Using the border ownership information, we automatically select fixation points inside all possible objects in the scene and segment them. Below is an example of our automatic segmentation process:
For details on how the fixation points are selected, refer to our page on "simple" objects and/or our paper in RSS 2011.
* Developed a touch free camera app 6pics to capture awesome selfies!
* Developed a camera app Kick2Click to capture pictures of kicking action.
* Details of my ECCV 2010 demo (Sep 2010) is available now!
- Active Visual Segmentation
Ajay K. Mishra, Yiannis Aloimonos, Cheong Loong Fah and Ashraf Kassim
IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), Vol 34, No. 2, April 2012.
- Active Segmentation
Ajay K. Mishra and Yiannis Aloimonos
International Journal of Humanoid Robotics (IJHR), Vol 6., pp 361-386, 2009.
- Segmenting "Simple" Objects Using RGB-D
Ajay K. Mishra, Ashish Srivastav and Yiannis Aloimonos
IEEE International Conference on Robotics and Automation, 2012.(accepted)
- Visual Segmentation of "Simple" Objects for Robots
Ajay K. Mishra and Yiannis Aloimonos
Robotics Science and Systems conference (RSS), 2011.
- Active Segmentation With Fixation
Ajay K. Mishra, Yiannis Aloimonos and Cheong Loong Fah
International Conference on Computer Vision (ICCV), 2009.
[PDF] [BIBTEX] [Webpage] [Segmentation Code] (New C++ source code released!!)
- Active Segmentation For Robotics
Ajay K. Mishra, Cornelia Fermuller and Yiannis Aloimonos,
International Conference on Intelligent RObots and Systems (IROS), 2009.
- Active Segmentation: A New Approach
Ajay K. Mishra, Yiannis Aloimonos
In Computational Vision: From Surfaces to Objects C. Tyler Ed., Chapman Hall and Hall/CRC Press, Chapter 2
- IMAGE SEGMENTATION: The view from inside the image
Ajay K. Mishra, Yiannis Aloimonos, Patrick, S.P. Wang(Ed.),
River Publishers, Pattern Recognition and Machine Vision, pp. 165-179, 2009
@ECCV in Greece, 2010
@U. of MD, Maryland Robotics Day. 2010
@NIST, Nov 29, 2010
@Willow Garage, Mar 01, 2010