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Repeat-Frame Selection Algorithm for Frame Rate Video Transcoding  [PDF]
Yi-Wei Lin,Gwo-Long Li,Mei-Juan Chen,Shu-Fen Huang
International Journal of Image Processing , 2010,
Abstract: To realize frame rate transcoding, the forward frame repeat mechanism is usuallyadopted to compensate the skipped frames in a video decoder for end-device.However, based on our observation, it is unsuitable for repeating all skippedframes only in the forward direction and sometimes the backward repeat mayprovide better results. To deal with this issue, we propose a new reference frameselection method to determine the direction of repeat-frame for skippedPredictive (P) and Bidirectional (B) frames. For P-frame, the non-zerotransformed coefficients and the magnitude of motion vectors are taken intoconsideration to determine the use of forward or backward repeat. For B-frame,the magnitude of motion vector and its corresponding reference directions of theblocks in B-frame are selected as the decision criteria. Experimental results showthat the proposed method provides 1.34 dB and 1.31 dB PSNR improvements inaverage for P and B frames, respectively, compared with forward frame repeat.
A Fast Multi-reference Frame Selection Algorithm for Multiview Video Coding  [cached]
Yuehou Si,Mei Yu,Zongju Peng,Gangyi Jiang
Journal of Multimedia , 2010, DOI: 10.4304/jmm.5.4.369-376
Abstract: Multiview video coding (MVC) plays an important role in three-dimensional video applications. Joint Video Team developed a joint multiview video model (JMVM) with multi-reference frame technology. Motion and disparity estimation are employed in multi-reference frame technology to provide better rate distortion performance. However, the process of searching blocks with variable sizes for motion and disparity estimation in multi-reference frames significantly increases the computational complexity. After analyzing the statistical features of multi-reference frames in MVC, this paper proposes a fast multi-reference frame selection algorithm based on a dynamic threshold technology correlated with the types of frames. All views of prediction structure in JMVM are categorized into three types, that is, the basic view without inter-view reference relation, the first layer views that only refer anchor frame from upper view, the second layer views that need to refer the basic view and the first layer views. Furthermore, all frames in MVC prediction structure are divided into three categories, the anchor frame without any reference, non-anchor frame in the base view and the first layer view, and the non-anchor frame in other views. Dynamic threshold technique is given to terminate the process of searching multi-reference frames early. The proposed algorithm also reduces the useless candidate reference frames by filtering out those reference frames that are less likely to contain the best matched results and achieves significant speed-up. Experimental results show that the proposed algorithm can achieve 50.13% ~ 72.19% reduction of encoding time in comparison with JMVM7.0, while the proposed algorithm hardly influences the rate distortion performance of MVC.
A Framework for the Assessment of Temporal Artifacts in Medium Frame-Rate Binary Video Halftones  [cached]
Rehman Hamood-Ur,Evans BrianL
EURASIP Journal on Image and Video Processing , 2010,
Abstract: Display of a video having a higher number of bits per pixel than that available on the display device requires quantization prior to display. Video halftoning performs this quantization so as to reduce visibility of certain artifacts. In many cases, visibility of one set of artifacts is decreased at the expense of increasing the visibility of another set. In this paper, we focus on two key temporal artifacts, flicker and dirty-window-effect, in binary video halftones. We quantify the visibility of these two artifacts when the video halftone is displayed at medium frame rates (15 to 30 frames per second). We propose new video halftoning methods to reduce visibility of these artifacts. The proposed contributions are (1) an enhanced measure of perceived flicker, (2) a new measure of perceived dirty-window-effect, (3) a new video halftoning method to reduce flicker, and (4) a new video halftoning method to reduce dirty-window-effect.
The Importance of Predictive and Face Validity in Employee Selection and Ways of Maximizing Them: An Assessment of Three Selection Methods  [cached]
Kelechi John Ekuma
International Journal of Business and Management , 2012, DOI: 10.5539/ijbm.v7n22p115
Abstract: The current exigencies and fluidity of the business environment engendered largely by demographic changes, technological advances and globalisation have made it imperative for organisations to posses the brightest talents as a source of competitive advantage, if they hope to survive. The continuing ‘talent war’ and fierce competition in the global market place; and issues concerning employee branding and candidate attraction, means that organisations and their managers have to carefully review their recruitment and selection processes, ensuring that employee selection methods not only contributes towards enhancing organisational image, but also predicts future job performance to a reasonable extent. There is therefore, the need for chosen methods to be high in both Predictive and Face validities. This article critically examines the importance of the concepts of Predictive and Face validities to employee selection in a wider context as an HR strategy and as an integral part of organisations’ general strategy, suggesting ways of improving both concepts. The central argument of this article, is that for selection methods to be effective, reliable, valid and minimise costs associated with loosing top talents, poor employee performance and turnover, it must possess high predictive and face value. The article assesses three major selection methods (interviews, work sampling and assessment centres) with a view of maximising their predictive and face validities, arguing that the design, contents and the manner of administrating these methods are major issues. The paper concludes that there is no one best way of selecting new employees, but a combination of carefully chosen methods and well-trained HR professionals will undoubtedly improve face and predictive validities and by extension, the selection method.
Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition  [PDF]
Yongkang Wong,Shaokang Chen,Sandra Mau,Conrad Sanderson,Brian C. Lovell
Computer Science , 2013, DOI: 10.1109/CVPRW.2011.5981881
Abstract: In video based face recognition, face images are typically captured over multiple frames in uncontrolled conditions, where head pose, illumination, shadowing, motion blur and focus change over the sequence. Additionally, inaccuracies in face localisation can also introduce scale and alignment variations. Using all face images, including images of poor quality, can actually degrade face recognition performance. While one solution it to use only the "best" subset of images, current face selection techniques are incapable of simultaneously handling all of the abovementioned issues. We propose an efficient patch-based face image quality assessment algorithm which quantifies the similarity of a face image to a probabilistic face model, representing an "ideal" face. Image characteristics that affect recognition are taken into account, including variations in geometric alignment (shift, rotation and scale), sharpness, head pose and cast shadows. Experiments on FERET and PIE datasets show that the proposed algorithm is able to identify images which are simultaneously the most frontal, aligned, sharp and well illuminated. Further experiments on a new video surveillance dataset (termed ChokePoint) show that the proposed method provides better face subsets than existing face selection techniques, leading to significant improvements in recognition accuracy.
Evaluation of Impairment Caused by MPEG Video Frame Loss  [PDF]
Carlos Alexandre Gouvea da Silva, Guilherme Fernandes de Souza Miguel, Jo?o Guilherme Sauer, Carlos Marcelo Pedroso
Engineering (ENG) , 2017, DOI: 10.4236/eng.2017.95029
Abstract: This article presents a study on the impact of video frame losses on the quality perceived by users. Video compression standards, such as MPEG, use a sequence of frames called Group of Pictures (GOP), which is a video compression method which a frame is expressed in terms of one or more neighboring frames. This dependence between frames impacts directly in the quality because a loss of a reference frame prevents the decoding of other frames in GOP, thereby reducing the user-perceived quality. The assessment of quality in this article is estimated by Peak Signal Noise Ratio (PSNR), which compares the original and the received images. Computer simulations were used to show that the degradation on the quality may vary for different patterns of GOPs and type of lost frames.
A Novel Approach Towards Keyframe Selection for Video Summarization
Chitra A. Dhawale,Sanjeev Jain
Asian Journal of Information Technology , 2012,
Abstract: For the short summary of large video, first step is to split the longer video into shots, then the representative frames (key-frames) for each shot are selected. These representative frames together form the video summary. In this study we have considered the video key-frame selection. As a part of research work and the minor research project, we have studied and implemented various methods for shot detection and key-frame selection using Matlab and C++. In this study the improved algorithm for histogram based approach is proposed for multiple visual descriptor features of video key-frames selection for compact video representation.
A Study of FR Video Quality Assessment of Real Time Video Stream  [PDF]
Xinchen Zhang,Lihau Wu,Yuan Fang,Hao Jiang
International Journal of Advanced Computer Sciences and Applications , 2012,
Abstract: To assess the real-time transmission video’s quality, this paper persents a approach which used FR video quality assessment (VQA) model to satisfy the objective and subjective measurement requirement. If we want to get the reference video in the measuring terminal and to make a assessment, there are two problems which are how to certain the reference video frame and how to make the objective score close to the subject assessment. We present in this paper a novel method of computing the order number of the video frame in the test point. In order to establish the relationship between the objective distortion and the subjective score, we used the “best-fit” regressed curve model and the BP neural network to describe prediction formula. This work is the mainly aim to get the high accurency assessment results with the human subjective feeling. So we select huge video sources for testing and training. The experimental results show that the proposed approach is suit to assess the video quality using FR model and the converted subjective score is available.
Optimal Frame Transmission for Scalable Video with Hierarchical Prediction Structure  [PDF]
Saied Mehdian,Ben Liang
Computer Science , 2013,
Abstract: An optimal frame transmission scheme is presented for streaming scalable video over a link with limited capacity. The objective is to select a transmission sequence of frames and their transmission schedule such that the overall video quality is maximized. The problem is solved for two general classes of hierarchical prediction structures, which include as a special case the popular dyadic structure. Based on a new characterization of the interdependence among frames in terms of trees, structural properties of an optimal transmission schedule are derived. These properties lead to the development of a jointly optimal frame selection and scheduling algorithm, which has computational complexity that is quadratic in the number of frames. Simulation results show that the optimal scheme substantially outperforms three existing alternatives.
A Fast Intra-frame Prediction Mode Selection Algorithm for H.264 Video Coding

LI Wen-jie,LI Gang,CAO Bin,WU Gong-wei,
,李刚 曹斌 吴功伟

中国图象图形学报 , 2009,
Abstract: In order to guarantee higher compression efficiency and video quality, a robust rate-distortion optimization(RDO) is employed in H.264/AVC video coding standard, which is jointly developed by ITUT and MPEG. According to the specification of RDO, all of the prediction modes have to be tried exhaustively in order to find the best mode. As a result, the computational complexity of the mode decision is extremely high and is not suitable for the real time service, such as video conference.This paper proposes a fast intra prediction modes decision algorithm based on the discrepancy within the video picture. In addition, the Direction-Vector based preferred modes selection method is introduced in the proposed algorithm to reduce the candidate modes to be tested. Experimental results are given to demonstrate that our proposed algorithm achieves a reduction of processing time by 40%~50% as compared with the current RDO optimized mode decision with little quality degradation.
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