News

Welcome New MCL Member Dr. Xiaoguang Li!

We are so happy to welcome a new Visiting Scholar, Dr. Xiaoguang Li, this Spring 2018. Let us hear what he would like to talk about his research and MCL.

1. Could you briefly introduce yourself and your research interests?

I am Xiaoguang Li, a teacher from Beijing University of Technology. I received my Ph. D degree in circuit and system from the Beijing University of Technology in 2008. I was a Research Assistant at Hong Kong Polytechnic University in 2006, 2007 and 2009 and a Visiting Scholar at the University of Sydney from Feb. to Jul. 2012. My research interests include image super resolution, face hallucination, high dynamic range image processing, and medical image analysis.

2. What is your impression about MCL and USC?

MCL is a large group with so many students. What surprised me is that the daily affairs of the laboratory are arranged in such an orderly manner. I think it should be thanks to the culture of MCL and the good self-organization of his members. I am also deeply influenced by Professor Kuo’s passion for his research.

The campus of USC is very beautiful.

3. What is your future expectation and plan in MCL?

I cherish the time in MCL very much. During this year, I would like to try my best to broaden my horizon, to consider my academic thoughts, and to improve my ability of doing high quality research. And as well as make friends with all the members of MCL. I appreciate Prof. Kuo for providing me with such a good opportunity to visit USC and MCL.

By |January 7th, 2018|News|Comments Off on Welcome New MCL Member Dr. Xiaoguang Li!|

Happy New Year – 2018

2017 has been a fruitful year for MCL. Some members graduated with impressive research work and began a new chapter of life. Some new students joined the MCL family and explored the joy of research. MCL members have made great efforts on their research and published quality research papers on top journals and conferences.

Wish all MCL members a happy new year.

Image credits: Photo 1: “2018 Happy New Year” by Yousef Maree, used under CC BY-SA 2.0 / Resized with white padding on the borders; Photo 2: “An Other Move to Success Happy New Year” by Salt Lake County Youth Services, used under CC BY-SA 2.0 / Resized with black padding on the borders.

By |December 29th, 2017|News|Comments Off on Happy New Year – 2018|

MCL Research Honored at APSIPA ASC 2017

The 9th Asia Pacific Signal and Information Processing Association (APSIPA) Annual Summit and Conference (ASC), or APSIPA ASC 2017 in short, was held in Kuala Lumpur, Malaysia, from Dec. 11-14, 2017. Research conducted at MCL has received a lot of attention at this conference.
First, MCL Director, Professor C.-C. Jay Kuo was the keynote speaker on December 14. The title of his talk is “Why Deep Learning Networks Work So Well?” His talk was very well attended. He received enthusiastic feedback from the audience. Although deep learning is very hot these days, there is little theoretical justification. Professor Kuo’s keynote provided insights into the working principle behind CNNs and also pointed out ways to improve its shortcomings by introducing the Saak transform.
Second, two MCL papers received honors at the conference. The paper entitled with “Understanding CNN via Deep Feature Analysis” by Hao Xu, Yueru Chen, Ruiyuan Lin and C.-C. Jay Kuo received the best paper award. The poster presentation on “Age/Gender Classification with Whole-Component Convolutional Neural Networks” (by Chun-Ting Huang, Yueru Chen, Ruiyuan Lin and C.-C. Jay Kuo) won the Springer best poster book prize. Both Hao Xu and Chun-Ting Huang were MCL alumni. Hao Xu is currently working at Google while Chun-Ting is a research engineer at Qualcomm.

By |December 18th, 2017|News|Comments Off on MCL Research Honored at APSIPA ASC 2017|

Welcome new MCL member Dr Chao Yang!

We are so happy to welcome a new Post Doctor, Dr Chao Yang, this Fall 2017. Let us hear what he has to say about his research and MCL.

1. Could you briefly introduce yourself and your research interests?

My name is Chao Yang, and I received my B.E and Ph. D degrees in Communication and Information Systems from Shanghai University, Shanghai, China in 2012 and 2017 respectively. I am currently a postdoctoral researcher at Media Communications Lab (MCL) in University of Southern California (USC) under the supervision of Prof. C.-C. Jay Kuo. My research interests include video compression and video processing.

2. What is your impression about MCL and USC?

I was impressed by the kindness and professional attitude of all members at MCL. The weekly seminars are beneficial for both the speakers and audience. The USC campus is very beautiful, and people here are very friendly, and they’ve gave me great help.

3. What is your future expectation and plan in MCL?

The Saak Transform is a very interesting and powerful tool, and I’d like to do some research with it, mainly in image/video compression. I hope to exceed my expectations under the supervision of Prof. C.-C. Jay Kuo. Also, I’d like to make friends with all MCL members.

By |December 15th, 2017|News|Comments Off on Welcome new MCL member Dr Chao Yang!|

Welcome new MCL member Dr Xinfeng Zhang!

We are so happy to welcome a new Post Doctor, Dr Xinfeng Zhang, this Fall 2017. Let us hear what he has to say about his research and MCL.

1. Could you briefly introduce yourself and your research interests?

My name is Xinfeng Zhang, and I received my B.S. degree in computer science from Hebei University of Technology, Tianjin, China, in 2007, and the Ph.D. degree in computer science from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, in 2014. From, Jul. 2014 to Oct. 2017, I was a research fellow in Rapid-Rich Object Search (ROSE) Lab in Nanyang Technological University, Singapore. My research interests include image/video compression, processing and quality assessment. I am also interested in image/video retrieval and analysis.

2. What is your impression about MCL and USC?

When I joined MCL, I was impressed with the professional group seminar, which is very formal and beneficial for both the speakers and audience. The active discussions among students also provide various views for us to think about questions. Moreover, I love the environment of USC, and it is real very beautiful.

3. What is your future expectation and plan in MCL?

I am very interested in the Saak transform, and I think it is a new powerful tool in image/video compression and understanding. Therefore, I hope to explore the characteristics of Saak transform, and investigate the higher compression performance using Saak transform. I also hope to become friends with all the other MCL members.

By |December 13th, 2017|News|Comments Off on Welcome new MCL member Dr Xinfeng Zhang!|

MCL celebrates Thanksgiving!

On November 23, MCL members and their respective families set out on a lavish Thanksgiving Luncheon organized by Professor Kuo at the China Great Buffet in El Monte. Thanksgiving has been an MCL tradition for over 20 years now, and this year was no exception. The spread was extremely satiating and diverse with an assortment of dishes including sushi, seafood, pizzas and dessert. All in all, it was a perfect start to a great holiday!

By |December 2nd, 2017|News|Comments Off on MCL celebrates Thanksgiving!|
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    MCL Student, Junting Zhang, Presented Paper at GlobalSIP 2017

MCL Student, Junting Zhang, Presented Paper at GlobalSIP 2017

MCL Student Junting Zhang presented a paper at the 5th IEEE Global Conference on Signal and Information Processing (GlobalSIP 2017) in Montreal Quebec, Canada on November 15, 2017. Here’s an abstract of the paper :
Scene text detection is a critical prerequisite for many fascinating applications for vision-based intelligent robots. Existing methods detect texts either using the local information only or casting it as a semantic segmentation problem. They tend to produce a large number of false alarms or cannot separate individual words accurately. In this work, we present an elegant segmentation-aided text detection solution that predicts the word-level bounding boxes using an end-to-end trainable deep convolutional neural network. It exploits the holistic view of a segmentation network in generating the text attention map (TAM) and uses the TAM to refine the convolutional features for the MultiBox detector through a multiplicative gating process. We conduct experiments on the large-scale and challenging COCO-Text dataset and demonstrate that the proposed method outperforms state-of-the-art methods significantly.

By |November 24th, 2017|News|Comments Off on MCL Student, Junting Zhang, Presented Paper at GlobalSIP 2017|
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    MCL Director, Professor Kuo, gave a Keynote Speech at ISPACS 2017

MCL Director, Professor Kuo, gave a Keynote Speech at ISPACS 2017

Professor C.-C. Jay Kuo gave a keynote speech in the IEEE Conference on Intelligent Signal Processing and Communication Systems held in Xiamen, China on November 7th. The title of his talk is “Why Deep Learning Networks Work So Well?” The abstract of his talk is given below.

“Deep learning networks, including convolution and recurrent neural networks (CNN and RNN), provide a powerful tool for image, video and speech processing and understanding nowadays. However, their superior performance has not been well understood. In this talk, I will unveil the myth of CNNs. To begin with, I will describe network architectural evolution in three generations: first, the McClulloch and Pitts (M-P) neuron model and simple networks (1940-1980); second, the artificial neural network (ANN) (1980-2000); and, third, the modern CNN (2000-Present). The differences between these three generations will be clearly explained. Next, theoretical foundations of CNNs have been studied from the approximation, the optimization and the signal representation viewpoints, and I will present main results from the signal processing viewpoint. A good theoretical understanding of deep learning networks provides valuable insights into the past, the present and the future of their research and applications.”

Understanding CNNs is one of the main activities of the MCL in last 3-4 years. Several PhD students and post-docs have made contributions to this topic, including Hao Xu and Yueru Chen.

By |November 19th, 2017|News|Comments Off on MCL Director, Professor Kuo, gave a Keynote Speech at ISPACS 2017|

Congratulations to Weihao Gan for passing his defense!

Let us hear what he has to say about his defense and an abstract of his thesis.

Online object tracking is one of the fundamental computer vision problems. It is commonly used in real world applications such as traffic control and safety in video surveillance, autonomous vehicle, robotic navigation, medical imaging, etc. It is a very challenging problem due to multiple time-varying attributes in video sequences.

In this research, we investigate two different kinds of tracking problems: single object tracking (SOT) and multiple object tracking (MOT). First, we attempt to achieve online single object tracking using both spatial and motion cues with two novel methods. One is a traditional framework called “temporal prediction and spatial refinement (TPSR)” tracker, consisting of three cascaded modules: pre-processing (PP), temporal prediction (TP) and spatial refinement (SR). Another one is based on convolutional neural network architecture that treats the tracking as a detection problem, called ”Motion-Guided Convolutional Neural Network (MGNet) Tracker”. It has two innovations: 1) adoption of a motion-guided candidate selection (MCS) scheme based on a dynamic prediction model, and 2) usage of a RGB- plus-motion 5-channel input to the convolutional neural network (CNN). From the two proposed methods, we have showed the advantages of combining spatial information and motion cue together to improve the tracking performance.

Second, from the proposed SOT technique, we build an online multiple object tracking system with advanced model update and matching. This method treats the MOT problem as an online tracking problem, rather than the global optimization framework. There are three major components in this tracking system: 1) a system platform built upon multiple CNN single object trackers in MOT environment; 2) the proposed advanced online update strategy including incremental and aggressive update mode; 3) [...]

By |November 14th, 2017|News|Comments Off on Congratulations to Weihao Gan for passing his defense!|

Welcome new MCL member Madhvi Kannan!

We are so happy to welcome a new master student, Madhvi Kannan, in Fall 2017. Let us hear what she said about her research and MCL.

1. Could you briefly introduce yourself and your research interests?

My name is Madhvi Kannan and I’m a Master’s Student in Electrical Engineering at USC. I joined MCL this Fall to work under Professor Kuo and his PhD student Ruiyuan Lin. My research interests include Image Processing and Deep Learning.

2. What is your impression about MCL and USC?

When I first joined MCL I was very excited to be exposed to the research being carried out by all the PhDs. I found that the research being conducted in MCL is up to date with the current trends in technology. The weekly seminars and study groups are extremely effective and novel.

3. What is your future expectation and plan in MCL?

​I hope to gain as much knowledge as possible in the fields of Image Processing, Computer Vision and Deep Learning during my term at MCL. I also look forward to learning from all the other lab members.

By |October 29th, 2017|News|Comments Off on Welcome new MCL member Madhvi Kannan!|