Monthly Archives: May 2014

MCLab Releases the New 3D Database: MCL-3D

Stereoscopic image/video contents have become popular nowadays. Since the multi-view image format is costly for visual communication, the 2D-image-plus-depth format is proposed as an alternative, where a texture image and its associated depth image are recorded at a view point simultaneously. For stereoscopic display, the depth image-based rendering (DIBR) technique is applied to the texture and depth images to generate the proper left and right views.

One critical issue regarding 3D-related applications is to develop a robust metric to assess the quality of 3D image (or video) stimuli. Although a good stereoscopic image quality assessment is much in need due to the emergence of 3D visual contents, most of stereoscopic image databases are still small and based on traditional stereo image format, that is, captured left and right images. This restricts the design of good objective quality metrics.

To tackle these limitations and facilitate the related research, MCLab has released a new 3D image database recently, which is called MCL-3D. This database is valuable for the following reasons. Firstly, the MCL-3D database adopts the 2D-image-plus-depth source, where stereoscopic images are synthesized by the DIBR rendering technique. Secondly, all stereo images in the MCL-3D database are of high resolution, which is closer to today’s real world applications. Finally, the database is downloadable online with the detailed description of the database generation and the corresponding subjective test. We hope that our MCL-3D database can help other researchers in developing a good quality assessment metric.

Download link:

By |May 25th, 2014|News|Comments Off on MCLab Releases the New 3D Database: MCL-3D|

Seven MCL Members Attending PhD Hooding Ceremony

Seven MCL members attended the Viterbi PhD hooding ceremony on Thursday, May 15, 2014, from 8:30-11:00 a.m. in the Bovard Auditorium. They were Martin Gawecki, Harshad Kadu, Hyunsuk Ko, Kuan-Hsien Liu, Tsung-Jung Liu, Sanjay Purushotham and Xue Wang. Congratulations to them and their families for their accomplishments in completing their PhD program at USC.

Martin Gawecki received a B.S. degree in Electrical Engineering from the University of California, Riverside (UCR) and an M.S. degree in Electrical Engineering from the University of Southern California (USC). Since 2009, he has been a member in the Media Communications Lab at USC, participating in the fields of statistical signal processing, machine learning, and time series analysis. His dissertation, entitled “A Signal Processing Approach to Robust Jet Engine Fault Detection and Diagnosis,” discusses the algorithms that can be used to advance engine health monitoring (EHM) with respect to data from vibration, acoustic, and classical (gas path) sensors. Done in conjunction with the Pratt-Whitney Institute for Collaborative Engineering (PWICE), his work demonstrates the superiority of vibration over acoustic sensors and showcases the ability of machine learning methods to assess performance of real engines based on fully simulated training data.

Harshad Kadu received his Bachelor’s degree from National Institute of Technology, Nagpur in 2008 and Master’s degree from University of Southern California, Los Angeles in 2011. Since then he has been pursuing his PhD in Electrical Engineering with Media Communications Lab at USC. His research interests include 3D human motion capture data analysis, image and music information processing, computer vision and statistical machine learning. His thesis titled ‘Advanced Techniques for Mocap Data Classification and Text Detection’ presents multi-resolution string representation based temporal and spatial domain techniques for human action recognition. His recent work [...]

By |May 18th, 2014|News|Comments Off on Seven MCL Members Attending PhD Hooding Ceremony|

MCLab Initiates Code Sharing Project

As algorithms become more and more complex, the implementations become more and more difficult. Without firsthand knowledge on the algorithm, it is extremely difficult and time consuming to build programs with respect to the publications. Many researchers are actively releasing their source code to the computer vision community these days. Their kindness gives great momentum to the development of better algorithms and the analysis on the existing approaches.

MCL wants to be a part of the selfless community by releasing all our research programs to the public. We are initiating the MCL Codebase Project, which aims at sharing our group member’s first hand implementations to the world. Since we are currently working on various researches, we will index them into five categories, including image/video quality assessment, face detection and recognition, scene recognition, object detection, image retrieval.

We will be offering projects through Github, so source codes are constantly updated and maintained. Anyone can easily branch either a stable version or a cutting edge development. The source code will be released under GNU General Public License, so researchers can use them freely. Researchers are welcome to contribute to our codebase. Send us a pull request and help us build a more powerful code base.

Our group member Hao Xu, Xiaqing Pan, and Chen Chen will serve as the MCL Codebase Project committee. Our senior group member Joe Lin, Sudeng Hu, and our group alumni Jiangyang Zhang will join the board of advisory. Professor Kuo will closely monitor the progress of this project.

By |May 11th, 2014|News|Comments Off on MCLab Initiates Code Sharing Project|
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    MCLab Inspires Cooperative Biomedical Research between USC and UCLA

MCLab Inspires Cooperative Biomedical Research between USC and UCLA

The Media Communication Lab (MCLab) at USC has a strong commitment to providing an interdisciplinary environment for student researchers, to nourish diversity of application of electrical engineering. Ph.D. candidate Xue Wang, whose research interest lies in biomedical and information processing, has been working on the validation of an evaluation tool for assessing surgical techniques. Capsulorhexis, which is a significant portion of cataract surgery, is of particular interest. Ongoing work on this problem has collaboration between faculty in the Ming Hsieh Department of Electrical Engineering at USC and the Jules Stein Eye Institute (JSEI) at UCLA since June of 2013.

The research aims at developing a valid set of quantitative and qualitative measures of surgical skills to accelerate the training of residents. Currently, capsulorhexis surgical techniques are assessed through an expert-panel-video-review using evaluation questions from the OSCAR and GRASIS evaluation tools.* However, there is considerable inter-observer variability, and direct quantitative questions were the least reliable. Xue’s work combines knowledge in biomedical image/video processing, machine learning, and computer vision to develop an automated quality assessment system to evaluate and improve surgical techniques, such that it is objective, accurate, and reliable. Human inspection is minimized along with the exploration of surgical video understanding via machine learning.

“It’s exciting to put focused and concerted effort in exploring the unknown and trying to find a solution for challenging problems. When you are working with excellent and talented people, you have a more open outlook on the potential of new cross-disciplinary methods”, Xue said. Xue’s work has been presented at AUPO and ASCRS conferences in January of 2014 and April of 2014, respectively.** Her result shows that video/image analysis provides an objective way to measure proficiency in the capsulorhexis part of cataract [...]

By |May 4th, 2014|News|Comments Off on MCLab Inspires Cooperative Biomedical Research between USC and UCLA|