Gaobo Yang

Identification of Motion-Compensated Frame Rate Up-Conversion Based on Residual Signals

Motion-compensated frame rate up-conversion (MC-FRUC) is originally presented to increase the motion continuity of low frame rate videos by periodically inserting new frames, which improves the viewing experience. However, MC-FRUC can also be exploited to fake high frame rate videos or splice two videos with different frame rates for malicious purposes. A blind forensics approach is proposed for the identification of various MC-FRUC techniques. A theoretical model is first built for residual signal, which is exploited as tampering trace for blind forensics. The identification of various MC-FRUC techniques is then converted into a problem of discriminating the differences of residual signals among them. A pre-classifier is designed to suppress the side effects of original frames and static interpolated frames in candidate videos. Then, spatial and temporal Markov statistics features are extracted from the residual signals inside the interpolated frames for MC-FRUC identification. Five open MC-FRUC softwares and six representative MC-FRUC techniques have been tested, and experimental results show that the proposed approach can effectively locate interpolated frames and further identify the adopted MC-FRUC technique for both uncompressed videos and compressed videos with high perceptual qualities.

Unimodal Stopping Model-Based Early SKIP Mode Decision for High-Efficiency Video Coding

High-efficiency video coding (HEVC) can greatly improve coding efficiency compared with the prior video coding standard H.264/AVC by adopting advanced hierarchical coding structures such as coding unit (CU), prediction unit (PU), and transform unit. For each CU, an exhaustive mode decision strategy is adopted to achieve the best rate distortion (RD) cost, which simultaneously results in enormous computational complexity. In this paper, an early SKIP mode decision algorithm is proposed for the HEVC encoder to speed up the process of mode decision. Each CU size is categorized into either rare used or frequent used by exploiting the correlation of CU depth, which is estimated from the temporally colocated CUs. For the rare-used CU size, the SKIP mode is directly selected as the optimal mode and the remaining mode decision process is early terminated. For the frequent-used CU size, a unimodal stopping model is designed for its early SKIP mode decision by exploiting both hierarchical mode structure and RD cost property. Experimental results show that the proposed early SKIP mode decision method achieves average 58.5% and 54.8% encoding time savings, while the Bjontegaard Delta bit rate only increases average 0.8% and 0.8% for various test sequences under the random access and the low delay B conditions, respectively.

Optical flow approximation based motion object extraction for MPEG-2 video stream

This paper presents a compressed-domain motion object extraction algorithm based on optical flow approximation for MPEG-2 video stream. The discrete cosine transform (DCT) coefficients of P and B frames are estimated to reconstruct DCxa0+xa02AC image using their motion vectors and the DCT coefficients in I frames, which can be directly extracted from MPEG-2 compressed domain. Initial optical flow is estimated with Black’s optical flow estimation framework, in which DC image is substituted by DCxa0+xa02AC image to provide more intensity information. A high confidence measure is exploited to generate dense and accurate motion vector field by removing noisy and false motion vectors. Global motion estimation and iterative rejection are further utilized to separate foreground and background motion vectors. Region growing with automatic seed selection is performed to extract accurate object boundary by motion consistency model. The object boundary is further refined by partially decoding the boundary blocks to improve the accuracy. Experimental results on several test sequences demonstrate that the proposed approach can achieve compressed-domain video object extraction for MPEG-2 video stream in CIF format with real-time performance.

Adaptive mode decision for multiview video coding based on macroblock position constraint model

Multiview video coding (MVC) exploits mode decision, motion estimation and disparity estimation to achieve high compression ratio, which results in an extensive computational complexity. This paper presents an efficient mode decision approach for MVC using a macroblock (MB) position constraint model (MPCM). The proposed approach reduces the number of candidate modes by utilizing the mode correlation and rate distortion cost (RD cost) in the previously encoded frames/views. Specifically, the mode correlations both in the temporal-spatial domain and the inter-view are modeled with MPCM. Then, MPCM is exploited to select the optimal prediction direction for the current encoding MB. Finally, the inter mode is early determined in the optimal prediction direction. Experimental results show that the proposed method can save 86.03xa0% of encoding time compared with the exhaustive mode decision used in the reference software of joint multiview video coding, with only 0.077xa0dB loss in Bjontegaard delta peak signal-to-noise ratio (BDPSNR) and 2.29xa0% increment of the total Bjontegaard delta bit rate (BDBR), which is superior to the performances of state-of-the-art approaches.

Early DIRECT Mode Decision for MVC Using MB Mode Homogeneity and RD Cost Correlation

Multi-view video coding (MVC) adopts variable size mode decision to achieve high coding efficiency. However, its high computational complexity is a bottleneck of enabling MVC into practical real-time applications. In this paper, an early termination strategy is proposed for DIRECT mode decision of MVC by exploiting mode homogeneity and rate distortion (RD) cost correlation. By comparing the RD cost between DIRECT mode and Inter

Adaptive Inter CU Depth Decision for HEVC Using Optimal Selection Model and Encoding Parameters

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A robust forgery detection algorithm for object removal by exemplar-based image inpainting

mode, an adaptive threshold is defined based on the MBs mode homogeneity and RD cost so as to early terminate the remaining inter and intra modes. Experimental results show that compared with the original JMVC model, the proposed approach can reduce the total encoding time from 65.08% to 91.45% (80.43% on average). Meanwhile, the Bjontegaard delta peak signal-to-noise ratio only decreases 0.031 dB and Bjontegaard delta bit rate increases 0.97% on average, which is a negligible loss of coding efficiency and superior to the performance of state-of-the-art methods.

Design of new scan orders for perceptual encryption of H.264/AVC videos

High efficiency video coding adopts a new hierarchical coding structure, including coding unit (CU), prediction unit (PU), and transform unit to achieve higher coding efficiency than its predecessor H.264/AVC high profile. However, its hierarchical unit partitioning strategy leads to huge computational complexity. In this paper, an adaptive inter CU depth decision algorithm is proposed, which exploits both temporal correlation of CU depth and available encoding parameters. An optimal selection model of CU depth is established to estimate the range of candidate CU depth by exploiting the temporal correlation of CU depth among current CU and temporally co-located CUs. To reduce the accumulated errors in the process of CU depth prediction, the maximum depth of the co-located CUs and the coded block flag (CBF) of the current CU are used. Moreover, PU size and CBF information are also used to decide the maximum depth for the current CU. Experimental results show that the proposed CU depth decision approach reduces 56.3% and 51.5% average encoding time, and the Bjontegaard delta bit rate increases only 1.3% and 1.1% for various test sequences under the random access and the low delay B conditions, respectively.

Hierarchical prediction-based motion vector refinement for video frame-rate up-conversion

Object removal is a malicious image forgery technique, which is usually achieved by exemplar-based image inpainting in a visually plausible way. Most existing forgery detection approaches utilize similar block pairs between inpainted area and the rest areas, but they invalidate when those inpainted images are further subjected to some post-processing operations such as JPEG compression, Gaussian noise addition and blurring. It is desirable to develop a forensic method which is robust to object removal with post-processing. From some preliminary experiments, we observe that post-processing destroys the similarity of block pairs and simultaneously disturbs the correlations among adjacent pixels to some extent. Inspired by the strong ability of joint probability density matrix (JPDM) in characterizing such correlation, we propose a hybrid forensics strategy. Firstly, our earlier method is employed to detect whether a candidate image is forged or not. Secondly, for those undetected images after the first step, JPDM is computed for each difference array to model the correlations among adjacent DCT coefficients, and the average of these matrixes are computed as feature vectors to further expose tampering traces. Experimental results show that the proposed approach can effectively detect object removal by exemplar-based inpainting either with or without post-processing.

Probability Model-Based Early Merge Mode Decision for Dependent Views Coding in 3D-HEVC

In this study, a perceptual encryption algorithm is proposed for H.264/AVC video to enhance the scrambling effect and encryption space. Six new scan orders are designed for H.264/AVC encoder by analysing the energy distribution of discrete cosine transform coefficients. They are proven to have similar performance as the conventional zigzag scan order and its symmetrical scan order. These six new scan orders are combined with two existing scan orders to design a scan-order based perceptual encryption algorithm. Specifically, video encryption is achieved more specifically by randomly selecting one scan order from the eight scan orders with a security key, and the sign bit flipping of DC coefficients is also incorporated to further increase the encryption space. Experimental results show that the proposed approach has the advantages of both low bitrate increase and low computational cost. Furthermore, it is more flexible and has stronger security than the existing scan-order based video encryption schemes.