siyangli

Last Thursday (Nov 27, 2014), Professor Kuo held a Thanksgiving luncheon for our MCL members at Ichiban Restaurant in El Monte. Around 35 people from our group including some family members and Professor Kuo’s family attended this great luncheon event at noon of Thanksgiving Day. There was a fusion of food such as Sushi, seafood, Chinese food, pizza and dessert, which was great for us since MCL has members from various regions. The most important thing was to have a social communication among our group. In this luncheon, everyone enjoyed talking to others and our topics were pretty diverse, ranging from research, course study, to sports, hobbies and Thanksgiving plans. Professor Kuo introduced his family to us and it was a great pleasure to receive warm Thanksgiving greetings from his family members. Besides, Professor Kuo went to each table to chat with group members, showing a touched concern about our life in the USA. Moreover, Professor Kuo’s sharing about his experience on research, PhD study, sociality, and life benefited us a lot on many aspects.

Two visiting scholars, Prof. Yang and Prof. Wang, mentioned this luncheon as “a valuable chance to understand the spirit of MCL group, to know the group members, and to learn more about Professor Kuo”. “My husband and I had no idea before about where to spend our Thanksgiving, but right now we find the answer is to have a good time with the big MCL family right here!”, as Dr. Nie told us. Yes! This is definitely correct. Most of our members are international students, whose families are quite far away. On this special moment, Thanksgiving Day, we just felt like we were a family right here, right now with [...]

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, [...]

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.

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 [...]

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.