Video super-resolution based on automatic key-frame selection and feature-guided variational optical flow

This paper proposes a new video super-resolution method based on feature-guided variational optical flow. The key-frames are automatically selected and super-resolved using a method based on sparse regression. To overcome the blocking artifacts and deal with the case of small structures with large displacement, an efficient method based on feature-guided variational optical flow is used to super-resolve the non-key-frames. Experimental results show that the proposed method outperforms the existing benchmark in terms of both subjective visual quality and objective peak signal-to-noise ratio (PSNR). The average PSNR improvement from the bi-cubic interpolation is 7.15 dB for four datasets. Thanks to the flexibility of designed automatic key-frame selection and the validness of feature-guided variational optical flow, the proposed method is applicable to various practical video sequences.     

互动新媒体中一种新型的通信业务应用——视频黄页

首先阐述视频黄页的概念,比较视频黄页与传统纸质黄页和基于互联网的黄页业务之间的优势和不足,然后介绍视频黄页的主要接入方式,描述各种接入方式下的业务流程,最后对全文进行总结。     

基于FPGA的双路视频信号的处理

本文介绍了一种采用FPGA实现双路视频信号的采集与处理技术。阐述了该系统的硬件设计与软件实现方案,实现双路视频信号的采样、合成及处理,包括多种模块的设计及功能仿真。     

Principal component analysis algorithm in video compressed sensing

An algorithm of principal component analysis in video compressed sensing is proposed in the paper. Aiming at the compressed sensing problems of video sequences, the inter-frame correlation among the images is analyzed and the transform coefficients with lower value are removed according to the energy concentration characteristics of principal component analysis. Therefore, the sparse realization of video signals in the form of principal component analysis is accomplished and the possibility of the transformation being used in compressed sensing algorithm is verified. Finally, simulation results show that, with the comparison of the traditional algorithm based on wavelet transform, the proposed algorithm can not only improve the reconstructed quality and the visual effects of the video sequence, but also save the sampling resources. Moreover, it is more suitable for stream transmission of multimedia.     

An efficient 3-dimensional discrete wavelet transform architecture for video processing application

This paper presents an optimized 3-D Discrete Wavelet Transform (3-DDWT) architecture. 1-DDWT employed for the design of 3-DDWT architecture uses reduced lifting scheme approach. Further the architecture is optimized by applying block enabling technique, scaling, and rounding of the filter coefficients. The proposed architecture uses biorthogonal (9/7) wavelet filter. The architecture is modeled using Verilog HDL, simulated using ModelSim, synthesized using Xilinx ISE and finally implemented on Virtex-5 FPGA. The proposed 3-DDWT architecture has slice register utilization of 5%, operating frequency of 396 MHz and a power consumption of 0.45 W.     

A self-adaptive optical flow method for the moving object detection in the video sequences

This paper proposes a self-adaptive optical flow method to detect moving objects in the video sequences. The method first estimates the original optical flow field with the optical flow algorithm, and then enhances the objects by a local mean algorithm, and finally filters out the noise with a self-adaptive threshold algorithm. The proposed method has a wide adaptivity to the size and the number of objects, and it also can effectively process the scenarios of complex background and that of the slight occlusion. Furthermore, it avoids the complicated and time-consuming preprocessing procedure. The results of the present method show that the moving objects can be detected effectively.     

基于内容的表示及其在远程教育系统中的应用

文章首先简要介绍了MPEG－4的基本思想和特点，基于内容的两种结构；然后介绍了三个使用基于内容表示的远程教育系统的实例，其中第三个例子是一个新颖的多媒体课件制作系统，这些例子说明了基于内容的表示特别适用于多媒体信息的描述，具有很好的应用前景。     

Future’s learning environments in health education: The effects of smart classrooms on the academic achievements of the students at health college

The aim of this study is to determine the effectiveness of smart classrooms on the academic achievement of the nursing students. The sample of the research included 66 Health College students in Elaz??. The sampling group was randomly chosen from second year students of Nursing and Midwife Education. The research was carried out with experimental approach. The experimental group included nursing students and the control group, midwife students. Pre-test and post-test including questions regarding “internal diseases’ course were applied to both groups. t-Test, percentage ands frequency were used as statistical procedures for data analysis. The findings showed that lectures given through smart classroom significantly increases the academic achievements of the students. It is, therefore, reasonable to state that smart classroom applications are effective environments that can be used as an alternative and a supplement to face to face educational environments in the institutions where health education is given.     

A perceptual scheme for fully automatic video shot boundary detection

In this paper, we propose a novel and robust modus operandi for fast and accurate shot boundary detection where the whole design philosophy is based on human perceptual rules and the well-known “Information Seeking Mantra”. By adopting a top–down approach, redundant video processing is avoided and furthermore elegant shot boundary detection accuracy is obtained under significantly low computational costs. Objects within shots are detected via local image features and used for revealing visual discontinuities among shots. The proposed method can be used for detecting all types of gradual transitions as well as abrupt changes. Another important feature is that the proposed method is fully generic, which can be applied to any video content without requiring any training or tuning in advance. Furthermore, it allows a user interaction to direct the SBD process to the user's “Region of Interest” or to stop it once satisfactory results are obtained. Experimental results demonstrate that the proposed algorithm achieves superior computational times compared to the state-of-art methods without sacrificing performance.     

Single–machine scheduling with random machine breakdowns and randomly compressible processing times

This work presents a model of single–machine scheduling problem. The machine is failure–prone and subject to random breakdowns. The processing time is a deterministic sequence that is randomly compressible, which may be from the introduction of new technology or addition of new equipment. Taking into account the cost for the random breakdowns and the random compressible processing time, our objective is to find the optimal scheduling policy to minimize an objective function. Under simple conditions, it is shown that the optimal sequence possesses a V-shape property