Monthly Archives: May 2015

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    MCLab Hosts a Visiting Student from Indian Institute of Technology Bombay

MCLab Hosts a Visiting Student from Indian Institute of Technology Bombay

The Viterbi-India program is jointly funded by the Indo US Science, Technology Forum (IUSSTF) and the USC VSoE. Each student in the Viterbi-India program will receive stipend and travel reimbursement. These students will come to USC and join one of the labs under EE department during May 20 and July 18, 2015.

After a competitive review process, there will be 20 spots for the Indian students in the program. Among those strong Indian students, Vikranth Reddy is the one who will join MCL in 2015 summer as an intern. We conducted a short interview with him about his previous experiences and future expectations.


1. Could you briefly introduce yourself? (Previous research/project experience, research interest and expertise)

I am Vikranth Dwaracherla, a third year undergraduate from IIT Bombay, India. I am currently pursuing my major in Electrical Engineering and minors in Computer Science. My previous research projects include neural networks, device simulations and image processing. I am very interested in the fields of computer vision and robotics. I have been working on a project on autonomous fruit collecting robot.

2.What was your first impression of USC and MCL?

USC is a wonderful place and provides opportunities for all people invariant of their interests. It is a wonderful place where people can pursue their goals. The members in the lab are all very kind and willing to help others. I would like to thank all the members of MCLab for the hospitality shown towards me.

3.What is your further expectation of being an MCL member?

I am very happy to be selected into the Viterbi- India Program and come to USC, one of the leading institutions in the field of Engineering and Technology. I am also very pleased to join MCLab, and to have the opportunity to work with [...]

By |May 31st, 2015|News|Comments Off on MCLab Hosts a Visiting Student from Indian Institute of Technology Bombay|

Congratulations to Xu (Becky) Qiu for Graduation with MSEE

Xu (Becky) Qiu, one of MCL members, graduated from USC on May 15, 2015. Congratulations to her and her families for her accomplishments in MCL and USC.

Xu (Becky) Qiu received her B.E. degree in Software Engineering from Shandong University (SDU), Jinan, China in 2011. Since 2013, she has been a research assistant in Media Communications Lab (MCL) at USC, advised by Prof. C.-C. Jay Kuo. Starting from Fall 2013, she served as a member of MCL Web Committee for a year, in charge of the alumni web page maintenances and updates. Becky was also the TA for a web design summer course for MCL interns in Summer 2014. In Fall 2014, she was the TA of Digital Image Processing (EE569). Since May 2014, she has been working on PWICE Google Glass Project as the team leader. On May 15, 2015, Becky Qiu got her M.S. degree in Electrical Engineering from University of Southern California (USC), Los Angeles.

By |May 24th, 2015|News|Comments Off on Congratulations to Xu (Becky) Qiu for Graduation with MSEE|

Five MCL Members Attended Viterbi PhD Hooding Ceremony

Five MCL members attended the Viterbi PhD hooding ceremony on Thursday, May 14, 2014, from 8:30-11:00 a.m. in the Bovard Auditorium. They were Sachin Chachada, Xiang Fu, Pang-Chang Lan, Sudeng Hu, and Joe Yuchieh Lin. Congratulations to them and their families for their accomplishments in completing their PhD program at USC.

Sachin Chachada received his B.E. degree in Electronics and Communication Engineering from S.R.K.N.E.C., RTM Nagpur University 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, and machine learning with applications to image and audio analysis. His dissertation, entitled “Environmental Sound Recognition: Classification and Retrieval,” discusses the algorithms that can be used to advance general audio understanding and management. His work demonstrates superior performance of ensemble learning algorithm for environmental audio classification, with use of classical, contemporary and a new set of time-frequency features. His work also includes novel algorithms for environmental sound retrieval for a large database, with promising applications for audio content management.

Xiang Fu received his B.S. degree in Electronic Engineering from Shanghai Jiao Tong University (SJTU), China in 2009, and his M.S. degrees in Electrical Engineering and in Computer Science, both from University of Southern California (USC), Los Angeles in 2011 and 2014, respectively. Since 2011, he has been pursuing his Ph.D. degree in Electrical Engineering with Media Communications Lab (MCL) at USC advised by Prof. C.-C. Jay Kuo, and has been working on various research areas including image/video segmentation, spectral clustering, visual tracking, object recognition, video surveillance, and machine learning. His dissertation, entitled “An Information Fusion Approach to Visual Data Segmentation”, discusses feature fusions [...]

By |May 17th, 2015|News|Comments Off on Five MCL Members Attended Viterbi PhD Hooding Ceremony|
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    USC and Netflix Joint Research to Be Presented at ICIP 2015 and ICME 2015

USC and Netflix Joint Research to Be Presented at ICIP 2015 and ICME 2015

Netflix ingest and encoding pipeline is a cloud-based platform that generates video encodes for the Netflix streaming service. Due to the large throughput of the system, automated video quality assessment of the source videos and the generated encodes is essential in ensuring the quality of experience of Netflix subscribers. Owing to the diversity of video content, traditional video quality assessment methods are not able to meet the need of Netflix video pipeline. A joint research team between USC MCL and Netflix is assembled to tackle this difficult problem.

A scalable solution of video quality assessment method is proposed by Joe Yuchieh Lin (USC), Eddy Chihao Wu (USC), Dr. Ioannis Katsavounidis (Netflix), Dr. Zhi Li (Netflix), Dr. Anne Aaron (Netflix), and Prof. C.-C. Jay Kuo (USC). This method is called Ensemble-Learning-based Video Quality Assessment Index (EVQA). EVQA adopts a frame-based learning mechanism to address the limited training data problem and fuses multiple image quality assessment indices to generate the final video quality score. The superior performance of the proposed EVQA index is demonstrated by experimental results conducted on both LIVE and MCL-V video databases.

The discussion of Netflix’s pipeline system, current solutions and remaining challenges will appear in ICIP 2015. The work of EVQA is accepted by ICME 2015 workshop on Cloud-based Media.

By |May 10th, 2015|News|Comments Off on USC and Netflix Joint Research to Be Presented at ICIP 2015 and ICME 2015|
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    MCL Research on Cross-Distance/Environment Face Recognition Accepted by CVPR Workshop on Biometrics

MCL Research on Cross-Distance/Environment Face Recognition Accepted by CVPR Workshop on Biometrics

Face recognition has been studied and developed for over decades. However, the long distance face recognition accompanied with automatic alignment is still a challenging topic due to its distorted and quality-degraded environment. This problem is also known as Face Recognition at A Distance (FRAD), which is a common issue in video surveillance applications.

A solution to FRAD has been proposed by MCL PhD student, Chun-Ting Huang, visiting scholar from UESTC, Professor Zhengning Wang, and Professor C.-C. Jay Kuo.  The method called Two-Stage Alignment/Enhancement Filtering (TAEF) system consists of three main components: a cross-distance face alignment technique, a cross-environment face enhancement technique, and a two-stage filtering system. In the first stage, the given probe image is adjusted and examined in coarse-scale for eliminating unlikely candidates, and then the procedure is conducted for every individual probe/gallery image pair for higher accuracy at the second stage. The first rank recognition rates of the TAEF method are 100%, 100% and 97% for 60-, 100- and 150-meter visible-light images in the LDHF database, respectively.

This work has been accepted for publication in the Computer Vision and Pattern Recognition (CVPR) 2015 Workshop on Biometrics held in Boston, June 11th, 2015.

By |May 3rd, 2015|News|Comments Off on MCL Research on Cross-Distance/Environment Face Recognition Accepted by CVPR Workshop on Biometrics|