Ivan V. Bajić

School of Engineering Science
Simon Fraser University
8888 University Drive
Burnaby, BC, V5A 1S6, Canada
T: +1-778-782-7159
F: +1-778-782-4951
E: ibajic@ensc.sfu.ca


I am a Professor of Engineering Science at Simon Fraser University. My professional interests revolve around signal processing, machine learning, and their applications in image and video processing, coding, communications, and multimedia ergonomics. In addition to research, teaching, and consulting in these areas, I was also involved in new media art as a Telepresence Architect for several telematic dance/music performances in 2009-2010.

I was born in Belgrade, Serbia, on February 18, 1976. I received the B.Sc.Eng. degree (summa cum laude) in Electronic Engineering from the University of Natal, South Africa, in 1998, and the M.S. degree in Electrical Engineering, the M.S. degree in Mathematics, and the Ph.D. degree in Electrical Engineering from Rensselaer Polytechnic Institute, Troy, NY, USA, in 2000, 2002, and 2003, respectively.

Besides professional life, I am also a wine enthusiast. I’ve been fortunate enough to visit some of the top wine producing regions in the world in the last number of years, including the Napa and Sonoma valleys in California, Cape Town/Stellenbosch region in South Africa, La Rioja in Spain, Douro valley in Portugal, Chianti in Italy and, closer to home, Okanagan and Cowichan valleys in British Columbia, as well as the Olympic Peninsula wineries in Washington State.


At SFU (2005 - present):

At UM (2003-2005):


My research interests are in the field of signal processing and its many applications. Signal processing is the science behind our digital life. In our work, my students, collaborators, and I, use the tools from signal processing, machine/deep learning, probability, statistics and optimization to analyze and solve problems related to all kinds of signals - images, video, audio, power - and others. Most of this work takes place at the SFU Multimedia Lab. Some of my ongoing application projects are listed below; please click on the corresponding image to learn more.

Multimedia ergonomics

The word ergonomics probably makes you think about comfortable chairs or pillows. But physical objects are not the only things we interact with. You likely spend a good portion of each day looking at images or video, listening to music, or browsing websites. Are these digital objects comfortable? We want to understand how people interact with digital objects, especially multimedia signals, in order to facilitate better user experience and more seamless interaction with our digital environment. Read more

Compressed vision

Remember the movie The Matrix, where software agents and trained human operators are able to spot objects and people from endless streams of digital data? Is this really possible? For humans, unlikely. But we have suceeded in training machines to do something like that. Being able to analyze compressed streams, without decoding, is one of the key technologies needed to handle massve amounts of video in the era of Big Data. Read more

Point clouds

Point clouds are sets of points in 3D space that describe the surface or shape of an object, and may carry additional attributes such as color. They were used for some time in computer graphics and animation industry, then 3D printing, and are now making their way towards mainstream through virtual/augmented reality and immersive media. Their irregular sampling makes their processing more challenging. Read more

Sound fields

Sound fields are acoustic counterparts of 3D video. They are essential for a covincing sense of immersion in virtual and augmented reality. Our work in this area is on spatial sound field control in noisy environments, array element placement, array signal processing, as well as study and design of loudspeaker and microphone array patterns. Read more

Computational sustainability

Computational sustainability tries to balance the needs of the environment, the economy, and society to solve sustainability problems using computational tools, models and algorithms. We are particularly interested in solving climate change and energy challenges through the theme of conservation and habitual change. To this end, we work with both academic and industry partners to develop and commercialize our discoveries and solutions. Read more

Current group members:

Research associates:


Former group members:

In industry:

In academia:

  • Md. Zulfiquar Ali Bhotto, Research Fellow at Nanyang Technological University, Singapore
  • Hadi Hadizadeh, Assistant Profesor at Quchan University of Advanced Technology, Iran
  • Sohail Bahmani, PostDoc at Georgia Tech
  • Sunghoon Ivan Lee, Assistant Professor of CS at UMass Amherst
  • Zhengguang Xie, Assistant Professor at Nantong University, China
  • Weidang Zhang, Professor at Zhengzhou University, China
  • Maxime Taquet, PostDoc at Harvard Medical School

Students' success:


Selected publications



















The software below is provided as is, without any warranty, expressed or implied. It is free for academic and non-commercial use. If you use the software in your research, please cite the corresponding references.

No-reference image quality assessment - A tool to evaluate image quality without a reference image. Download. (for password, please send an e-mail with your name and affiliation to hadi.sfu@gmail.com)
How many bits does it take for a stimulus to be salient? - Implementation of saliency estimation in video based on Operational Block Description Length (OBDL). Download.
Attention retargeting by color manipulation - Implementation of an attention retargeting method based on color manipulation. Download.
Subliminal flicker - Experiments with subliminal flicker to guide attention in natural images. Download.
Compressed-domain correlates of fixations in video - Implementation of visual saliency estimation methods for compressed video from the following two papers.
Download PIVP code.
Download MTAP code.
Saliency-aware video compression - Implementation of saliency-aware video compression from the following paper. Download.
Motion visualization in compressed video - Matlab code to reproduce the results from the following paper. Download.
NDLT-based compressed-domain GME - Matlab code for compressed-domain Global Motion Estimation (GME) based on the Normalized Direct Linear Transform (NDLT) algorithm. Download.
Compressed-domain tracking - Matlab code to reproduce the results from the following paper. Download.
Joint global motion estimation and motion segmentation - Matlab code to reproduce the results from the following paper. Download.
Outlier removal for global motion estimation - Matlab code for removing motion vector (MV) outliers from the MV field prior to global motion estimation. Download.
NAL-SIM - An interactive simulator of H.264/AVC video coding and transmission. Allows the user to encode a raw YUV video into H.264/AVC bitstream using a variety of options, analyze the bitstream structure (NAL units), simulate the loss of NAL units, and see the effects of loss on the decoded video quality. Download.
mcl.jit - A library of external objects for video coding, processing, and communication in Max/MSP/Jitter developed under the New Media Initiative grant funded by NSERC and CCA. A separate web page is maintained for it. Web.

Region-based predictive decoding of video - A Windows executable implementing Xvid MPEG-4 video encoding, and Region-Based Predictive Decoding (RBPD) of the resulting MPEG-4 video bitstreams. Download.
Error concealment for MC-EZBC - Microsoft Visual C/C++ code for motion-compensated error concealment for MC-EZBC. It includes an early version of MC-EZBC submitted to MPEG in 2002. Current versions of MC-EZBC are available on the CIPR website. Download.
NXSensor - Nucleosome eXclusion Sequence sensor is a tool for finding regions of DNA sequences that are likely to be nucleosome-free. The basic idea behind NXSensor is that the DNA sequence which wraps around the nuclosome needs to have a certain degree of flexibility. DNA flexibility is a necessary (though not the only, and also not sufficient) condition for nucleosome formation. It is known that the intrinsic curvature of a piece of DNA depends on its sequence, and we use that knowledge to find DNA sequences that are fairly rigid. Regions of DNA that have several rigid sequences close to each other are likely to be nucleosome-free. Web.
Maximum minimal distance lattice partitioning (MMDLP) - Matlab code for generating a partition matrix that solves the constrained sphere packing problem on the Z2 lattice. Download.
Dispersive Packetization (DP) for images - Microsoft Visual C/C++ code for dispersive packetization of subband/wavelet coded images. Baseline coder is based on Geoff Davis' Kit, with the packetization and error concealment modules added. Download.

The datasets below are provided without any warranty, expressed or implied. They are free for academic and non-commercial use. If you use the data in your research, please cite the corresponding references.

Eye tracking database for standard video sequences - This dataset includes a database of gaze locations by 15 independent viewers on a set of 12 standard CIF video sequences: Foreman, Bus, City, Crew, Flower Garden, Mother and Daughter, Soccer, Stefan, Mobile Calendar, Harbor, and Tempete. Included are the gaze locations for the first and second viewing of each sequence, their visualizations, heat maps, and sample MATLAB demo files that show how to use the data.


Segmented foreground objects - This dataset includes manually segmented foreground objects that we used as the ground truth in our moving region segmentation. Each set contains segmentation masks, segmented object(s), and original frames.


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Design based on http://getskeleton.com/