Profile

I received my Ph.D in Information Science and Technology from the University of Tokyo, Japan in 2013, MS in Computer System Engineering from GIK Institute of Engineering Sciences and Technology, Pakistan in 2006 and BE in Software Engineering from Army Public College of Management and Sciences (APCOMS), Pakistan in 2004.

Primarily my research interests are in the field of computer vision with focus on the acquisition, modeling and synthesis of complicated real world phenomenon which usually falls in the sub-domain of physics based vision. Besides this I also have research interests in several related areas of computer vision which are both of applied and theoretical nature. In the past my research work focused on extracting/embedding meaningful information from/in videos and images and in recent years on the measurement, modelling and synthesis with applications in many real world tasks and scenarios.  

My Ph.D work was on the development of efficient BRDF and SVBRDF acquisition and modeling methods which has since led me to focus on the development of rapid acquisition and modelling systems in recent years.

Since the Fall of 2014, I have been involved with Gravisc Inc. which designs and develops the necessary hardware and software for rapid acquisition and modeling systems with the objective of providing robust and low cost solutions to diverse set of industries . The developed solutions focus on different areas of measurement and modelling in computer vision and strive to be the state of the art in the field making various real world measurement tasks significantly easier.  

A research statement summarizing some of the things that I have worked on in the last several years can be read here: research statement (short). I am also a member of IEEE and ACM.

Research Highlights

Updates

• Evaluate Easily is now available for use by instructors globally as a limited public beta in phase two trials. The product has been developed with the aim to provide access to quality evaluation tools and methods to everyone. The platform brings you one of the finest systems available online for conducting in class, online or remote evaluations quickly and easily. While I usually work in a different subject area the Evaluate Easily platform has been developed to facilitate the wider academic community irrespective of whether their universities, colleges and institutes have provided them access to such facilities or not.

• The Multipurpose Data Acquisition Platform (MULDAP) which is a state of the art proprietary hardware platform for facilitating rapid acquisitions of data for wide range of tasks involving light matter interactions is now available through Gravisc Inc. It is an extremely portable platform which can be used for precise and accurate measurements of data for tasks such as 3D Scanning/Modeling, BRDF and SVBRDF measurements (isotropic, anisotropic, bivariate), Multispectral and Hyperspectral Imaging, Subsurface Scattering, projector camera systems and numerous other tasks. For more information please refer to the company page.

• BRDF data of four paint samples measured in high dynamic range using the methods described in our [ACCV 12] and [IPSJ 13] papers is now available. The binary files available for download follow the MERL BRDF dataset format and can be used with the same settings: [brown-metallic-paint], [apricot-paint], [white-glossy-paint], [reflection-diffuse-paint]. Renderings of these materials can be seen here.

• Hyperspectral images of an object measured in the visible spectrum from 400nm to 720nm along with the accuracy evaluation are available for download. The work is part of the rapid acquisition and modeling system: hyperspectral-images, accuracy-evaluation.pdf

• 3D models of three objects measured using the simultanous shape and BRDF measurement process in point cloud format (ply) are available here: [decoration.ply][monster.ply] [fox.ply]

• Dataset and code of several papers and related implementations is now available in the source code and dataset section.

Publications

Journals

Book Chapter

Conferences

• 1. Asad Ali, "Efficient Appearance Modeling of Objects with Planned Sampling", Technical Report, Sato Lab, Institute of Industrial Science, University of Tokyo, April 2013 

  2. Asad Ali, I. Sato, T. Okabe, Y. Sato, “Optimal Sampling for Efficient BRDF Acquisition”, IPSJ Computer Vision and Image Media (CVIM), Special Interest Group (SIG) and IEICE Technical Report, page 1-8, January 2013

  3. Asad Ali, “Simultaneous Estimation of Object Shape and BRDF with Planned Sampling”, Technical Report, Sato Lab, Institute of Industrial Science, University of Tokyo, December 2012.

  4. Asad Ali, “Efficient Acquisition of BRDFs using Linear Basis Representation”, Technical Report, Rinko Seminar, Department of Information and Communication Engineering (ICE), Graduate School of Information Science and Technology, University of Tokyo, November 2011

  5. Asad Ali, “Material Recognition: A Review”, Technical Report, Rinko Seminar, Department of Information and Communication Engineering (ICE), Graduate School of Information Science and Technology, University of Tokyo, November 2010

Awards 

• Japanese government MEXT scholarship for PhD studies at the University of Tokyo, 2010-2013

• Pakistan government scholarship for MS studies at GIK Institute of Engineering Sciences & Technology, 2004-2006

• 2nd Best Paper Award in IEEE International Conference on Emerging Technologies (ICET 06), November, 2006

• 2nd Prize in All Pakistan Software Competition (SOFTCOM 03) held at GIK Institute, September, 2003  [DAWN News article Cached] 

Services

• Reviewed Papers of IEEE Transactions on Systems Man & Cybernetics Part C: Applications & Reviews

• Reviewed Papers of Journal of Systems & Software (Elsevier)

• Technical Committee Member  IEEE ICET 2014 

The source code and datasets provided below are for research and educational purpose only and appropriate citation to the research paper(s) where mentioned in the code and/or this website should be included. This is only a partial list and a more elaborate listing of source code and datasets is available here. You can also refer to the Mathworks File Exchange Central community profile for additional code and YouTube Page for demo videos.

General Links: Sato Lab, Institute of Industrial Science, Department of Information and Communication Engineering, 

Graduate School of Information Science and Technology, The University of Tokyo, National Institute of Informatics (NII)

Computer Vision & Other Useful Links: Middlebury Evaluations and Datasets, Peter Kovesi Computer Vision Codes, Genetic Programming Toolbox

Last Update: May 2023