Entity

Time filter

Source Type

Haidian, China

Beijing Film Academy is a coeducational state-run higher education institution in Beijing, China. The film school is the largest institution specialising in the tertiary education for film and television production in Asia. The academy has earned international recognition for its achievements in film production. Wikipedia.


Ma H.,Beijing Film Academy | Wu G.,Tsinghua University
International Journal of Visual Design | Year: 2013

The Olympic Games are global events that aim to build a more peaceful and better world through supporting and promoting the spirit of fair play in sport. The Olympic Mascot carries the symbolic meaning of the Olympic Games; yet, it also represents the cultural heritage of the host city. How to blend local culture with the Olympic spirit and realize them in a global event is the major concern when designing an Olympic Mascot. One of the Authors of this paper is the original concept designer of the Beijing 2008 Olympic mascot. This paper documents the inspiration which led to the original concept of the 2008 Olympic mascot design, and describes in detail how traditional Chinese culture was adapted to reflect the Olympic spirit in the evolution of the mascot design. It also shows how to blend local Chinese culture effectively with global recognition, and realize local attraction in a global event. © Common Ground. Source


Zhang L.,Peking University | Zhao X.,CAS Institute of Computing Technology | Zhao X.,University of Chinese Academy of Sciences | Ma S.,Peking University | And 3 more authors.
Journal of Visual Communication and Image Representation | Year: 2011

This paper presents a novel intra prediction algorithm, named position-dependent filtering (PDF), to improve the intra prediction accuracy. Different from the existing schemes where the samples along one prediction direction are predicted with the same set of filtering coefficients, in the proposed PDF, position-dependent filtering coefficients are employed, i.e., different sets of filtering coefficients are pre-defined for samples with different coordinates in one coding block. For each intra prediction mode, the set of linear filtering coefficients for each position within one block is obtained from off-line training using the least square method. Moreover, to further reduce the algorithm complexity, a simplified PDF (sPDF) is proposed. In sPDF, only a subset of reference samples are used for prediction and the others are discarded because of the minor contribution to intra prediction. The proposed algorithm has been implemented in the latest ITU-T VCEG KTA software. Experimental results demonstrate that, compared with the original KTA with new intra coding tool enabled, up to 0.53 dB of average coding gain is achieved by the proposed method, while applicable computational complexity is retained for practical video codecs. © 2010 Elsevier Inc. All rights reserved. Source


Xiao H.J.,Tsinghua University | Xiao H.J.,Beijing Film Academy | Ji X.Y.,Tsinghua University | Dai Q.H.,Tsinghua University
Science China Information Sciences | Year: 2012

In multi-user video (MUV) delivery scenarios, the available resources of receiver devices, such as processing capability, link packet error rate (PER), and bandwidth, are usually different. We propose a relay-assisted hierarchical adaptation (RHA) scheme to maximize the total perceptual quality of all users when transmitting video streams coded via scalable video coding (SVC). First, MUV bitstreams are adaptively extracted under the constraints of network bandwidth and individual decoding capacity. Next, the relay links are introduced as substitutes of possible bad direct links for packets retransmissions. Approximately equal opportunity of transmission is allocated to each stream while the packets inside a stream are scheduled according to their priorities. The priorities are determined by the links states and packets loss distortions. Simulation results show that our RHA scheme has significant performance improvements compared with other schemes. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg. Source


Hu H.,Hefei University of Technology | Yang J.,Hefei University of Technology | Zhu L.,Beijing Film Academy | Xi H.,Hefei University of Technology
Information and Control | Year: 2013

An energy conservation optimal control approach is proposed for multimedia server cluster systems based on Markov switching state space control model. First the stochastic control model is introduced for multimedia server cluster systems. Under this model, the energy conservation control problem is formulated as a constrained optimization problem. Based on Lagrange multipliers method and performance potential theory, an online policy iterative algorithm is proposed. The algorithm solves the optimal control policy on-line by sample path and the solving procedure does not need any accurate system parameter information. Simulation experiments demonstrate the effectiveness of the proposed approach. Source


Zhang Y.,Beijing University of Posts and Telecommunications | Yue T.,Beijing University of Posts and Telecommunications | Wang H.,Beijing University of Posts and Telecommunications | Wei A.,Beijing Film Academy
Proceedings - 17th IEEE International Conference on Computational Science and Engineering, CSE 2014, Jointly with 13th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2014, 13th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2014 and 8th International Conference on Frontier of Computer Science and Technology, FCST 2014 | Year: 2015

In this paper, we attempt to predict users' quality of experience (QoE) with the log data collected from the web sites of Internet video service providers. To this end, we first collect service log data in the wild from one of the Top 5 most popular providers in China. Then we do a series of data preprocessing to format the original semi-structured log data to structured. We calculate several key video quality metrics, such as join time and frame rate, and explore the distributions of each quality metric, as well as the relationship between individual quality metric and user engagement. Considering that user engagement may be a result of comprehensive effect of several metrics, we apply fuzzy decision tree (FDT), a kind of classification algorithms in the area of machine learning, to develop the predictive model of user QoE for Internet video. Finally, we compare the prediction accuracy of our model with the model developed using decision tree on several different datasets. Our model separately achieves about 20% and 10% improvement in prediction accuracy on the dataset of sessions with the same content type and the dataset of sessions with mobile access devices. © 2014 IEEE. Source

Discover hidden collaborations