Inter frame

About: Inter frame is a research topic. Over the lifetime, 4154 publications have been published within this topic receiving 63549 citations.

Fast and accurate motion estimation algorithm by adaptive search range and shape selection

Abstract: The paper presents a fast and accurate motion estimation algorithm. To obtain accurate motion vectors while minimizing computational complexity, we adjust the search range for each frame and each block to suit the motion level of the video. An appropriate search range for each frame is determined on the basis of motion vectors and prediction errors obtained for the previous frame. At each block, the search range is determined on the basis of the search range of its frame and of the motion vector values of all adjacent blocks for which those values have already been obtained. With our algorithm, since narrow search ranges are chosen for areas in which little motion occurs, computational complexity can be reduced without degrading estimation accuracy. Since wide search ranges are chosen for areas of significant motion, good video-quality encoding can be maintained. In the encoding of an SDTV size video, the addition of range adjustment results in a reduction in the computational complexity of motion estimation of roughly 65%, while maintaining the same video quality.

A Fast MB Mode Decision Algorithm for MPEG-2 to H.264 P-Frame Transcoding

Abstract: The H.264 standard achieves much higher coding efficiency than the MPEG-2 standard, due to its improved inter-and intra-prediction modes at the expense of higher computational complexity. Transcoding MPEG-2 video to H.264 is important to enable gradual migration to H.264. However, given the significant differences between the MPEG-2 and the H.264 coding algorithms, transcoding is a much more complex task and new approaches to transcoding are necessary. The main problems that need to be addressed in the design of an efficient heterogeneous MPEG-2/H.264 transcoder are: the inter-frame prediction, the transform coding and the intra-frame prediction. In this paper, we focus our attention on the inter-frame prediction, the most computationally intensive task involved in the transcoding process. This paper presents a novel macroblock (MB) mode decision algorithm for P-frame prediction based on machine learning techniques to be used as part of a very low complexity MPEG-2 to H.264 video transcoder. Since coding mode decisions take up the most resources in video transcoding, a fast MB mode estimation would lead to reduced complexity. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264 video have a correlation with the distribution of the motion compensated residual in MPEG-2 video. We use machine learning tools to exploit the correlation and construct decision trees to classify the incoming MPEG-2 MBs into one of the several coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. Experimental results show that the proposed approach reduces the MB mode selection complexity by as much as 95% while maintaining the coding efficiency. Finally, we conduct a comparative study with some of the most prominent fast inter-prediction methods for H.264 presented in the literature. Our results show that the proposed approach achieves the best results for video transcoding applications.

Motion Histogram Analysis Based Key Frame Extraction for Human Action/Activity Representation

Abstract: Key frame extraction is an important technique in video summarization, browsing, searching, and understanding. In this paper, a novel algorithm for key frame extraction based on intra-frame and inter-frame motion histogram analysis is proposed. The extracted key frames contain complex motion and are salient in respect to their neighboring frames, and can be used to represent actions and activities in video. The key frames are first initialized by finding peaks in the curve of entropy calculated on motion histograms in each video frame. The peaked entropies are then weighted by inter-frame saliency which we use histogram intersection to output final key frames. The effectiveness of the proposed method is validated by a large variety of real-life videos.

Motion compensated predictive coding

Abstract: Motion compensated predictive codingS. Kappagantula and K. R. RaoDepartment of Electrical Engineering, The University of Texas at ArlingtonP.O. Box 19016, Arlington, Texas 76019AbstractInterframe image coding techniques in real -time provide a very attractive scheme of reduc-ing the bandwidth required for coding and transmitting natural video scenes. This paper pro-poses a modification of two existing algorithms for motion compensated interframe coding.It is shown that the modified method involves a reduced computational complexity while beingcompatible with the performance obtained by the previous algorithms. Implementation of thenew algorithm is consequently simplified and a design for the hardware using a parallelprocessing approach is studied. The system is proposed for use in NTSC TV pictures forapplications ranging from broadcast quality TV to video teleconferencing systems.IntroductionInterframe techniques in image coding present one of the most attractive schemes ofexploiting redundancy in natural video scenes. Conventional interframe techniques were fora long time restricted to coding the television image in terms of clusters of interframedifferences. Here each current frame is compared with the previous frame and only the dif-ferences are coded and transmitted. The receiver simply adds these differences to a copy ofthe previous frame that it has stored. This method has been shown to achieve reductions ofthe order of a factor of 10 over full bandwidth transmission. However as the televisionpicture displays increasing amounts of motion, the coding efficiency of this technique fallsoff rapidly. Such a deficiency makes the method unsuitable for TV transmission at very lowbit rates. Typical TV scenes involve motion details in particular sections of the imagewhile other areas can be said to be 'stationary' or unchanging areas. Moreover the motiondetail that the picture contains, varies with different pictures. Interframe motion compensa-t4.on techniques have therefore evolved2-4,6 -21 where the motion of each pel of a new frame(or a group of pels) is 'predicted' from the information available in the previous frame.Motion compensated predictj,o19L §chemes of this sort can be divided into two types pelrecursive algorithms (PRA) and (ii) block matching algorithms (BMA).

Motion wake identification and control mechanism

Abstract: The present invention provides a system and method for detecting macroblocks of a video frame that are located in one or more motion wake regions of the video frame. In one embodiment, a motion wake engine is configured to select a subset of macroblocks comprising non-peripherally located macroblocks selected to be inter-coded with motion vector magnitudes less than a predetermined motion vector threshold. Then, the motion wake engine identifies which macroblocks of the subset of macroblocks are located in first, second, third, or fourth motion wake regions of the video frame based upon a motion vector analysis of nearest neighbor macroblocks. In another embodiment of the invention, the motion wake engine applies error concealment/video improvement techniques to the identified macroblocks for video error concealment and for reducing visual artifacts associated with the motion wake regions.