Education

  • Ph.D. 2012-Present

    Ph.D. in Computer Graphics

    University of California Irvine, School of Information and Computer Sciences

  • M.S.2012-2014

    Master of Science in Computer Science

    University of California Irvine, School of Information and Computer Sciences

  • B.S.2007-2012

    Bachelor of Science in Computer Engineering

    Sharif University of Technology

Work Experience

A Practical Method for Fully Automatic Intrinsic Camera Calibration Using Directionally Encoded Light

Mahdi Abbaspour Tehrani, Thabo Beeler, Anselm Grundhofer
Conference PapersComputer Vision and Pattern Recognition (CVPR), Honolulu, Hawaii, July 2017. (Selected as Spotlight Paper)

Abstract

Correcting perceived perspective distortions using object specific planar transformations

Mahdi Abbaspour Tehrani, Aditi Majumder, M.Gopi
Conference PapersInternational Conference of Computational Photography (ICCP), Evanston, IL, USA, May 2016.

Abstract

Distortions due to perspective projection is often de- scribed under the umbrella term of foreshortening in com- puter graphics and are treated the same way. However, a large body of literature from artists, perceptual psycholo- gists and perception scientists have shown that the percep- tion of these distortions is different in different situations. While the distortions themselves depend on both the depth and the orientation of the object with respect to the camera image plane, the perception of these distortions depends on other depth cues present in the image. In the absence of any depth cue or prior knowledge about the objects in the scene, the visual system finds it hard to correct the foreshortening automatically and such images need user input and external algorithmic distortion correction.

High-Resolution Lighting of 3D Reliefs Using a Network of Projectors and Cameras

Behzad Sajadi, Mahdi Abbaspour Tehrani, Mehdi Rahimzadeh, Aditi Majumder
Conference Papers 3DTV, Lisbon Portugal, 2015. (Best Paper Award)
image

Abstract

Vibrant lighting of relief maps via high-resolution dynamic projected imagery can be a powerful tool for simulation, augmented reality, and visualization, enabling several scientific, educational and entertainment applications. This is usually achieved via multiple projectors lighting the relief map, which are then sensed by multiple cameras for geometric and color calibration. However, cumbersome semi-automatic calibration techniques have limited the applicability of such systems.

In this paper we present the first fully-automatic lighting system that registers high-resolution images on arbitrarily-shaped relief maps using a network of projectors and cameras. The devices are uncalibrated and casually aligned with the only constraint that every surface point of the relief is seen by at least two of the cameras. Our method achieves precise geometric registration followed by seamless edge blending. Quick recalibration allows changes in the position and number of the devices, as well as the surface geometry. Thus, our work can enable easy deployment of spatially augmented reality environments in various scales playing a fundamental role in increasing their popularity in several applications like geospatial analysis, architectural lighting, cultural heritage restoration, theatrical lighting and visualization. It can also be applied to any immersive VR environments on non-planar surfaces like domes or cylinders.

Undistorting Foreground Objects in Wide Angle Images

Mahdi Abbaspour Tehrani, Aditi Majumder, M.Gopi
Conference PapersIEEE International Symposium on Multimedia (ISM), Anaheim, CA, USA, 2013.

Abstract

An approximation algorithm for finding skeletal points for density based clustering approaches

Soheil Hassas Yeganeh, Jafar Habibi, Hassan Abolhassani, Mahdi Abbaspour Tehrani, Jamshid Esmaelnezhad
Conference Papers Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM, part of the IEEE Symposium Series on Computational Intelligence, pp. 403-410, Nashville, TN, USA, 2009.

Abstract

Clustering is the problem of finding relations in a data set in an supervised manner. These relations can be extracted using the density of a data set, where density of a data point is defined as the number of data points around it. To find the number of data points around another point, region queries are adopted. Region queries are the most expensive construct in density based algorithm, so it should be optimized to enhance the performance of density based clustering algorithms specially on large data sets. Finding the optimum set of region queries to cover all the data points has been proven to be NP-complete. This optimum set is called the skeletal points of a data set. In this paper, we proposed a generic algorithms which fires region queries at most 6 times the optimum number of region queries (has 6 as approximation factor). Also, we have extend this generic algorithm to create a DBSCAN (the most well- known density based algorithm) derivative, named ADBSCAN. Presented experimental results show that ADBSCAN has a better approximation to DBCSAN than the DBRS (the most well-known randomized density based algorithm) in terms of performance and quality of clustering, specially for large data sets.

Automatic pill identification

M.Abbaspour, E.Asgari, S.Bagheri, M.N.Do, P.Khanipour, J.Lu, S.Mahabadi, A.Vakilian
Technical Report ADSC technical report, pp. 1 - 16, Oct. 2010.

Indoor positioning and navigation with a camera phone

M.Abbaspour, E.Asgari, S.Bagheri, M.N.Do, P.Khanipour, J.Lu, S.Mahabadi, A.Vakilian
Technical Report ADSC technical report, pp. 1 - 10, Oct. 2010.

Work Experiences

  • Summer 2016

    Intern at Disney Research Lab

  • Summer 2015

    Software Engineer Intern at Ooma

  • Summer 2014

    Software Engineer Intern at SRHC2

    Geo Search: Implementing and integrating high performance geo search into SRCH2 keyword search engine.

    Access Control List: Implementing record-based access-control for the SRCH2 search engine.

  • Jul-Sep 2013

    Intern (Researcher) at Beckman Laser Institute (BLI)

    Developing a 3D tracking software for the breast cancer detection probe.

  • Jun-Jul 2013

    Software Engineer Intern at Digital Raster

    Design and development of plugins for MAYA(3D Animation Software).

  • Summer 2010

    Intern at ADSC (Advance Digital Sciences Center)

    Joint research center between UIUC and A*STAR, Singapore. Worked on the project E-CAM: Efficient Visual Computing for Interactive Vision Applications on Mobile Devices. Worked on two project:

    Indoor Positioning and Navigation with Camera Phone.
    Pill Identification with Camera Phone.

Academic Experiences

  • Spring 2009

    Presenter for Algorithmic Graph Theory study group

    Under the supervision of Prof. Mo- hammad Ali Safari

  • 2015 2013

    Teaching Assistant at UC Irvine

    Computer Graphics
    Visual Computing
    Artificial Intelligence
    Boolean Algorithms
    Introduction to Programming

  • 2012 2007

    Teaching Assistant at Sharif University of Technology

    Signals and Systems
    Design and Analysis of Algorithms
    Theory of Languages and Automata
    System Analysis and Design
    Advanced Programming