Improved fast intra prediction algorithm of H.264/AVC

With advanced prediction modes of intra prediction, intra coding of H.264/AVC offers significant coding gains compared with previous video coding standards. It uses an important tool called Lagrangian rate-distortion optimization (RDO) technique to decide the best coding mode for a block, but the computational burden is extremely high. In this paper, we proposed an improved fast intra prediction algorithm including block type selection and mode decision algorithm based on analysis of edge feature of a block. Our algorithm filters out unlikely block type and candidate modes to reduce the RDO calculations. Experimental results showed that the proposed algorithm can reduce the computation complexity of intra prediction from 52.90% to 56.31%, with 0.04 dB PSNR degradation and 2% increase of bit rate.     

Triadic interaction in clinical task-based interviews with mathematics teachers

A clinical task-based interview can be seen as a situation where the interviewer–interviewee interaction on a task is regulated by a system of explicit and implicit norms, values, and rules. This paper describes how documenting and mapping triadic interaction among the interviewer, the interviewee, and the knowledge negotiated can be used to increase procedural replicability of the interview and accuracy of drawn conclusions about the interviewee’s thinking process. Excerpts from interviews with 25 inservice mathematics teachers working on a task to make up a problem whose solution requires division of two fractions are discussed. The excerpts illustrate the relationship between methodological decisions taken by the interviewer during the interview and the applicability of the interview output to the research questions. A divergent analysis of the interviews with these teachers, which spanned over two years and were conducted by four interviewers, is used to offer a framework for analyzing data collected in clinical task-based interviews.     

基于核密度估计多样性采集的背景建模算法

1IntroductionBackground subtraction methods are extensively ex-ploited for moving object detection in videos in manyapplications ,such as traffic monitoring[1],human mo-tion capture[2]and video surveillance[3]. The centralidea behind such methods is to segment foreground ini mage sequences taken from a fixed camera by com-paring each newframe to a model of the scene back-ground . Therefore , correctly and efficiently modelingand updating the background model is one of the mostchallenging aspec…