Inter frame

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

Motion filtering for video stabilization

Abstract: For applying a motion filter of a video stabilization system to a sequence of video frames, an estimate of a motion in the current video frame compared to a first video frame of the sequence of video frames is received. Based on the received motion estimate and on at least one state variable of the motion filter, a correction value for the motion in the current video frame is computed. The at least one state variable is updated in the computation. In case the computed correction value exceeds a system constraint of the video stabilization system, the at least one state variable is adjusted in accordance with an extent by which the system constraint is exceeded. The correction value is then recomputed based on the motion estimate and on the adjusted state variable .

Inter-frame forgery detection in H.264 videos using motion and brightness gradients

Abstract: In the midst of low cost and easy-to-use multimedia editing software, which make it exceedingly simple to tamper with digital content, the domain of digital multimedia forensics has attained considerable significance. This research domain deals with production of tools and techniques that enable authentication of digital evidence prior to its use in various critical and consequential matters, such as politics, criminal investigations, defense planning. This paper presents a forensic scheme for detection of frame-based tampering in digital videos, especially those captured by surveillance cameras. Frame-based tampering, which involves insertion, removal or duplication of frames into or from video sequences, is usually very difficult to detect via simple visual inspection. Such forgeries, however, disturb the temporal correlation among successive frames of the tampered video. These disturbances, when analyzed in an appropriate manner, help reveal the evidence of forgery. The forensic technique presented in this paper relies on objective analysis of prediction residual and optical flow gradients for the detection of frame-based tampering in MPEG-2 and H.264 encoded videos. The proposed technique is also capable of determining the exact location of the forgery in the given video sequence. Results of extensive experimentation in diverse and realistic forensic set-ups show that the proposed technique can detect and locate tampering with an average accuracy of 83% and 80% respectively, regardless of the number of frames inserted, removed or duplicated.

Pixel-Based Inter Prediction in Coded Texture Assisted Depth Coding

Abstract: This letter presents a pixel-based motion estimation scheme assisted with the coded texture video for depth inter-prediction, in view of motion similarity between depth and texture video. The proposed scheme can achieve higher inter-prediction gain without transmitting any motion vector in the pixel-based motion estimation. Coupled with depth-texture structure similarity, the inter prediction method is further extended to an integrated prediction approach by making use of both intra and inter information. Experimental results show that our proposed method achieves superior rate-distortion performance.

Low-Complexity Heterogeneous Video Transcoding Using Data Mining

Abstract: Recent developments have given birth to H.264/AVC: a video coding standard offering better bandwidth to video quality ratios than previous standards (such as H.263, MPEG-2, MPEG-4, etc.), due to its improved inter- and intraprediction modes at the expense of higher computation complexity. It is expected that H.264/AVC will take over the digital video market, replacing the use of previous standards in most digital video applications. This creates an important need for heterogeneous video transcoding technologies from older standards to H.264. In this paper, we focus our attention on the interframe prediction, the most computationally intensive task involved in the heterogeneous video transcoding process. This paper presents a novel macroblock (MB) mode decision algorithm for interframe prediction based on data mining techniques to be used as part of a very low complexity heterogeneous video transcoder. 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 the decoded video. We use data mining tools to exploit the correlation and derive decision trees to classify the incoming decoded 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. For general validation purposes, we apply our algorithm to two of the most important heterogeneous video transcoders: MPEG-2 to H.264 and H.263 to H.264. Our results show that the our data-mining based transcoding algorithm is able to maintain a good video quality while considerably reducing the computational complexity by 72% on average when applied in MPEG-2 to H.264 transcoders, and by 62% on average when applied in H.263 to H.264 transcoders. Finally, we conduct a comparative study with some of the most prominent fast interprediction methods for H.264 presented in the literature. Our results show that the proposed data mining-based approach achieves the best results for video transcoding applications.

Temporal decomposition and inverse temporal decomposition methods for video encoding and decoding and video encoder and decoder

Abstract: Temporal decomposition and inverse temporal decomposition methods using smoothed predicted frames for video encoding and decoding and video encoder and decoder are provided. The temporal decomposition method for video encoding includes estimating the motion of a current frame using at least one frame as a reference and generating a predicted frame, smoothing the predicted frame and generating a smoothed predicted frame, and generating a residual frame by comparing the smoothed predicted frame with the current frame.