News

Interview with Visiting Scholar Prof. Chenhui Yang

In November 2014, MCLab has a new visiting scholar, Professor Chenhui Yang. Prof. Yang is Professor at School of Information Science and Technology, Xiamen University, Xiamen, China. We are glad to have an interview with him, talking about his previous research experiences and future expectations at USC.

 

1. Could you briefly introduce yourself and describe your previous research experience?

I come from Xiamen University (XMU), one of the ten most beautiful universities in China. Before joining XMU in 1995, I received my Bachelor and Master degrees from NUDT (National University of Defense Technology) in 1989 and 1992 respectively, and Ph.D. from Zhejiang University (ZJU). My academic research areas include intelligent multimedia technology and data mining. Specific research topics include video-audio analysis, image recognition, 3D reconstruction, 3D printing, 3D simulation, big data mining and clouding computing. I am also interested in finding computational solution to some problems from other disciplines, such as intelligent transportation and security, bioinformatics, health and medical informatics, smart city, and computational sociology, etc. I also co-founded two start-ups. Though I did not succeed in entrepreneurship, I still have a strong ambition to invent something helpful in the future.

 

2. What is your first impression of USC and MCLab?

USC is very large and deeply internationalized, considering the diversity of students, faculties, architecture styles and campus culture. What I love most is the interdisciplinary programs and groups. Professor Kuo and the MCLab are world widely famous. I was surprised that MCLab manages to keep thriving while some other academic groups are shrinking in such a tide of financial crisis. Prof. Kuo is one of the best professors I know, who has creative ideas, lasting passion, rich experiences and deep love to his students. All MCLab members are very bright, enthusiastic, [...]

By |November 16th, 2014|News|Comments Off on Interview with Visiting Scholar Prof. Chenhui Yang|
  • Permalink Gallery

    New Results on Objective Quality Index for Retargeted Images Presented at ACM MM

  • OLYMPUS DIGITAL CAMERA

New Results on Objective Quality Index for Retargeted Images Presented at ACM MM

Content-aware image retargeting is a technique that resizes images for optimum display on devices with different resolutions and aspect ratios. Traditional objective quality of experience (QoE) assessment methods are not applicable to retargeted images because the size of a retargeted image is different from its source. Dr. Jiangyang Zhang, a former MCL member and Professor C.-C. Jay Kuo, MCL Director, identified three main determining factors for humans visual QoE on retargeted images. They are global structural distortion (G), local region distortion (L) and loss of salient information (S). Zhang and Kuo selected features to quantify these respective distortion degrees and developed objective quality assessment index, called GLS, to predict viewers’ QoE by fusing selected features into one single quality score. The proposed GLS quality index has stronger correlation with human QoE than other existing objective metrics in retargeted image quality assessment with respect to two subjective image retargeting quality databases. The work was presented in the ACM Multimedia Conference on November 5 in Orlando, Florida.

A joint photo of Dr. Zhang and Prof. Kuo and a photo of Prof. Kuo together with ACM MM conference organizers and a Keynote Speaker, Prof. Rosalind Picard of MIT Media Lab (number 3 from the right), are shown.

By |November 9th, 2014|News|Comments Off on New Results on Objective Quality Index for Retargeted Images Presented at ACM MM|
  • Permalink Gallery

    MCL Collaborates with Cardiovascular Engineering Research Laboratory (CERL) in UCLA and Cardiovascular Genetics Clinic (CGC) in UCSD

MCL Collaborates with Cardiovascular Engineering Research Laboratory (CERL) in UCLA and Cardiovascular Genetics Clinic (CGC) in UCSD

MCL director Prof. C. -C. Jay Kuo is collaborating with CERL director Prof. Tzung Hsiai and CGC director Dr. Neil Chi to study how genetic programming is associated with congenital heart disease. They will study the heart development of the embryos of live zebrafish. The embryos of live zebrafish had Gata1a morpholino oligonucleotides (MO) micro-injection reduced erythropoiesis, which reduced viscosity by 70%. CERL research associate Dr. Peng Fei used single plane illumination microscopy (SPIM) technique to scan 1000 x-y frames in each plane from the top end of the zebrafish heart to the bottom end. MCL PhD student Hao Xu developed period determination, synchronization, and alignment algorithm to reconstruct 4-dimentional model (3-dimentional model over time) based on SPIM captured image sequences. CERL PhD candidate Juhyun Lee will use Amira to compute wall boundary conditions of the 4-dimentional model and introduce 3-dimentional Computation Fluid Dynamics (CFD) to simulate wall shear stress (WSS). The initial results have been published in BMES [1].

MCL is glad that its advanced image processing algorithm development capacity can be used to assist cardiovascular research. MCL will continue provide useful image processing tools that works in various areas of research.

[1]. Juhyun Lee, Peng Fei, Hao Xu, Chih-ming Ho, C.-C. Jay Kuo, Neil Chi and Tzung Hsiai, “Linking between cardiac trabeculation development and wall shear stress with 4-dimenstional single plane illumination microscopy,” Biomedical Engineering Society (BMES) annual meeting, San Antonio, Texas, USA, October 22-25, 2014.

By |November 2nd, 2014|News|Comments Off on MCL Collaborates with Cardiovascular Engineering Research Laboratory (CERL) in UCLA and Cardiovascular Genetics Clinic (CGC) in UCSD|
  • Permalink Gallery

    Professor Kuo’s Keynote Speech at LEAP 3.0 Annual Conference on Big Data

Professor Kuo’s Keynote Speech at LEAP 3.0 Annual Conference on Big Data

MCL Director, Professor C.-C. Jay Kuo, gave a keynote speech at the LEAP 3.0 annual conference at the USC Davidson Conference Center at 1:50-2:50pm, October 25 (Saturday), 2014. LEAP is the acronym of “Leadership, Excellence, Aspiration and Platform”, which is a career development forum series launched in 2013. It is co-founded by the Chinese-American Engineers and Scientists Association of Southern California (CESASC) and Southwestern Chinese Students and Scholars Association (SWCSSA). The purpose of the LEAP conferences is to provide a professional networking platform for Chinese students and Chinese American professionals throughout their overseas studies and professional careers.

In his speech, Professor Kuo first gave an overview on big data science and engineering. He pointed out two big data industrial sectors: 1) big data infrastructure providers and 2) big data service providers. Although there will be a steady growth in the sector of big data infrastructure providers, he emphasized the value and opportunities in the sector of big data service providers. Furthermore, he elaborated on several key technologies in big data analytics, including machine learning, data mining, speech understanding and computer vision. At the end of his talk, Professor Kuo made a prediction by saying that “the coming decade (2015-2025) would be the golden decade for the computer vision researchers since quite a few major breakthroughs would come out and lay the foundation of modern computer vision.” Professor Kuo also answered several questions from the floor. The keynote was well received.

By |October 26th, 2014|News|Comments Off on Professor Kuo’s Keynote Speech at LEAP 3.0 Annual Conference on Big Data|

Interview with visiting scholar Dr. Zhengning Wang

In October 2014, MCLab has a new visiting scholar, Dr. Zhengning Wang. Dr. Wang is Associate Professor at School of Electronic Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China. We are glad to have an interview with him, talking about his previous research experiences and future expectation at USC.

 

Could you please give an introduction about yourself and your previous research?

I received my Ph.D degree from Southwest Jiaotong University, Chengdu, China in 2007. In 2008, I joined University of Electronic Science and Technology of China and there I worked with about five graduate students. From 2009 to 2011, I worked as a post-doctoral fellow in the second research institute of Civil Aviation Administration of China (CAAC), where I served as a project leader on remote control tower. My research focus is image/video processing, especially video coding, multimedia communication and image enhancement. I also have research experiences in ground surveillance and guidance in air traffic control, video codec design, target tracking for security, light field data compression and high performance computing based on GPU.

 

What is your impression about MCLab and USC?

MCLab has a good atmosphere and I was impressed by the hardworking of the group members. They are also quite friendly and warm-hearted. I received lots of help from Xiaqing, Jian and other group members. USC is a well-known university for her top-notch academic achievements. Researchers here collaborate with each other and exchange their ideas actively, making a perfect opportunity to gain academic communication experiences.

 

What is your expectation and plan in the following academic year?

I hope to work closely with Prof. Kuo to facilitate our research projects. Besides research, I plan to learn about course organization and teaching from USC. I wish [...]

By |October 19th, 2014|News|Comments Off on Interview with visiting scholar Dr. Zhengning Wang|
  • Permalink Gallery

    Professor Kuo’s Keynote Speech at the Optoelectronic Imaging and Multimedia Technology Conference

Professor Kuo’s Keynote Speech at the Optoelectronic Imaging and Multimedia Technology Conference

MCL Director, Professor C.-C. Jay Kuo, gave a keynote speech at the Optoelectronic Imaging and Multimedia Technology Conference, part of 2014 Photonics Asia Program, on October 10, 2014, in Beijing International Convention Center, Beijing, China.

The title of Professor Kuo’s speech was “Big visual data analysis: challenges and solution strategies”. Due to the huge size and great diversity of visual data, big visual data analytics plays a critical role in applications such as large-scale image/video indexing, search and tagging. In this work, Professor Kuo addressed two competing factors that have a high impact on the performance of a classification system; namely, data diversity and data abundance. He presented two strategies to handle the data diversity problem – data grouping and decision stacking. Once the data diversity problem is well resolved, the solution will benefit from data abundance since more data samples allow a learning-based classifier to offer better performance. Professor Kuo used an indoor/outdoor scene classification problem to show the power of the proposed techniques in handling big visual data.

The Optoelectronic Imaging and Multimedia Technology Conference was chaired by Professor Qionghai Dai of Tsinghua University while Photonics Asia was co-organized by the International Society for Optics and Photonics (SPIE) and the Chinese Optical Society (COS). It was the largest annual event showcasing photonics and optical technologies and applications in Asia.

By |October 12th, 2014|News|Comments Off on Professor Kuo’s Keynote Speech at the Optoelectronic Imaging and Multimedia Technology Conference|
  • Permalink Gallery

    Large-scale indoor/outdoor image classification via expert decision fusion

Large-scale indoor/outdoor image classification via expert decision fusion

Scene understanding has been a hot topic in computer vision research fields for quite a long time. As a sub-branch of scene understanding, indoor/outdoor scene classification has become increasingly challenging throughout the years as visual data becomes larger and more diverse. As existing approaches are not scalable to large-scale visual data (usually 100,000 images at least), it is extremely important to have an accurate and robust system to handle big visual data for robust indoor/outdoor classification applications.
Mr. Chen Chen and Ms. Yuzhuo Ren, two MCL PhD students, and Professor C.-C. Jay Kuo recently proposed a new framework to tackle the large-scale indoor/outdoor image classification problem via an expert decision fusion system. The proposed solution has been tested on a large-scale and the most challenging scene understanding dataset from the SUN database, and a correct classification rate of 91.2% has been achieved, which is the state-of-the-art technique in the field. This work has been accepted for publication in the 1st Scene Understanding for Autonomous Systems Workshop (SUAS 2014) held in conjunction with ACCV 2014, Singapore, November 2, 2014.

By |October 5th, 2014|News|Comments Off on Large-scale indoor/outdoor image classification via expert decision fusion|

Research on Human Mocap Data Classification

The increasing demand for rendering smooth and plausible 3D motion is fueling the development of motion capture (mocap) systems. This new format of high quality 3D motion data has paved its way into animation movies, high-end computer games, biomechanics and robotics (see the accompanying photo from [1]). Diverse applications and the rapid development of mocap systems have resulted in a large corpus of data in recent years. Automatic classification of the mocap data is essential for various database management tasks such as segmentation, indexing and retrieval.

Mr. Harshad Kadu, a MCL PhD student, and Professor C.-C. Jay Kuo recently proposed a new framework to tackle the human mocap data classification problem using novel spatial/temporal feature representations, machine learning and decision fusion concepts. The proposed solution methods are tested on a wide variety of sequences from the CMU mocap database, and a correct classification rate of 99.6% is achieved, which is the state-of-the-art technique in the field. This work has been accepted for publication in the IEEE Trans. on Multimedia.

[1] http://www.noldus.com/innovationworks/content/automated-behavior-recognition-in-humans

By |September 30th, 2014|News|Comments Off on Research on Human Mocap Data Classification|

Interview with new MCL postdoctoral Xue Wang

Xue Wang, a recently graduated Ph.D. student from Media Communications Lab at USC, decides to continue her research work as a postdoctoral associate here with us. She is so happy to study with Professor Kuo and other lab members. Now we have an interview with her, talking about the change of roles between a Ph.D. student and a post-doc researcher and lifelong study plan.

Could you briefly describe yourself and your current research?

My research is an extension of the previous work on the objective evaluation of cataract surgical techniques using image processing and computer vision methods. The state-of-art surgeon evaluation tools primarily require human observers to fill out a grading questionnaire after viewing a video of the procedure, a technique that is subject to observer bias and variability. Therefore, it is hoped that our work could be extremely helpful in developing reliable computational analysis methods that can precisely and automatically identify quantitative and qualitative evaluation for surgical techniques.

Why do you choose to take a post-doc position and what’s your future plan?

I set up my career goal to become a faculty in the university when I started my Ph.D. at USC. I enjoy doing research and communicating with fellow workmates, and working as a post-doc is necessary step in the preparation for becoming faculty. To make this decision, I talked with different professors about the ongoing research work and future plan. Also, I got great help from Jing Zhang, one of our MCLab alumni, who is now pursuing her post-doc at Yale University. I’d apply for faculty position in future and I need to improve myself more. One aspect is about the research; I will enhance my work and try to seize any off-campus presentation opportunity [...]

By |September 21st, 2014|News|Comments Off on Interview with new MCL postdoctoral Xue Wang|

Interview with new MCL visitor Jeong Seyoon

Dr. Seyoon Jeong, a principal researcher in Broadcasting and Telecommunications Media Research Laboratory of Electronics and Telecommunications Research Institute (ETRI), have been visiting Media Communications Lab (USC) since this September. Now we have an interview with him, talking about his research and thoughts on MCLab.

Could you briefly describe yourself and your previous research experience?

I received BS, MS degrees from Inha University in 1995, and 1997, respectively. Then I finished my Ph.D degree from Korea Advanced Institute of Science and Technology (KAIST) in Aug. 2014. Since December 1996, I joined ETRI and focused on the development of international standards such as Scalable Video Coding (SVC), High Efficient Video Coding (HEVC). Currently, my research interests are video coding, super resolution and parallel computing for realistic broadcasting applications such as 3DTV and UHDTV.

What were your first impression of USC and MCLab?

I just arrived USC this month and not very familiar with the environment. People in the lab are very nice and help me a lot. I met Hyunsuk Ko this Monday. He showed me around the campus and our lab. USC is a very diverse university. People from all over the world come to here for their dreams. It is amazing that happens to meet some Koreans when walking on campus and chats with them, just like at home.  As for Media Communications Lab, it is a big family. Professor Kuo is very warm-hearted to introduce his group to me. I really like his style that treats his students as his children. I feel so lucky to join this group.

What is your future expectation in MCLab?

Actually, this is the second year of the UHDTV collaborative project from ETRI and USC MCLab. For the first year, Dr. Kim [...]

By |September 15th, 2014|News|Comments Off on Interview with new MCL visitor Jeong Seyoon|