基于局部线性嵌入的视频拷贝检测方法

该文提出了基于局部线性嵌入(LLE)的视频哈希方法,该方法首先利用一个图模型选取代表帧,然后以四阶累积量作为视频在高维空间的特征并利用LLE对视频进行降维,利用视频在3维空间中投影点的范数构造视频哈希序列来实现视频拷贝检测。实验证明该方法具有较好的鲁棒性和区分性。     

Robust semi-blind video watermarking based on frame-patch matching

In this paper, we present a frame-patch matching based robust semi-blind video watermarking using KAZE feature. The KAZE feature is employed for matching the feature points of frame-patch with those of all frames in video for detecting the embedding and extracting regions. In our method, the watermark information is embedded in Discrete Cosine Transform (DCT) domain of randomly generated blocks in the matched region. In the extraction process, we synchronize the embedded region from the distorted video by using KAZE feature matching. Based on the matched KAZE feature points, RST (rotation, scaling, translation) parameters are estimated and the watermark information can be successfully extracted. Experimental results show that our proposed method is robust against geometrical attacks, video processing attacks, temporal attacks, and so on.     

Deep chroma prediction of Wyner–Ziv frames in distributed video coding of wireless capsule endoscopy video

Compression of captured video frames is crucial for saving the power in wireless capsule endoscopy (WCE). A low complexity encoder is desired to limit the power consumption required for compressing the WCE video. Distributed video coding (DVC) technique is best suitable for designing a low complexity encoder. In this technique, frames captured in RGB colour space are converted into YCbCr colour space. Both Y and CbCr representing luma and chroma components of the Wyner–Ziv (WZ) frames are processed and encoded in existing DVC techniques proposed for WCE video compression. In the WCE video, consecutive frames exhibit more similarity in texture and colour properties. The proposed work uses these properties to present a method for processing and encoding only the luma component of a WZ frame. The chroma components of the WZ frame are predicted by an encoder–decoder based deep chroma prediction model at the decoder by matching luma and texture information of the keyframe and WZ frame. The proposed method reduces the computations required for encoding and transmitting of WZ chroma component. The results show that the proposed DVC with a deep chroma prediction model performs better when compared to motion JPEG and existing DVC systems for WCE at the reduced encoder complexity.     

Adaptive weighted fusion with new spatial and temporal fingerprints for improved video copy detection

In this paper, we propose a new and novel modality fusion method designed for combining spatial and temporal fingerprint information to improve video copy detection performance. Most of the previously developed methods have been limited to use only pre-specified weights to combine spatial and temporal modality information. Hence, previous approaches may not adaptively adjust the significance of the temporal fingerprints that depends on the difference between the temporal variances of compared videos, leading to performance degradation in video copy detection. To overcome the aforementioned limitation, the proposed method has been devised to extract two types of fingerprint information: (1) spatial fingerprint that consists of the signs of DCT coefficients in local areas in a keyframe and (2) temporal fingerprint that computes the temporal variances in local areas in consecutive keyframes. In addition, the so-called temporal strength measurement technique is developed to quantitatively represent the amount of the temporal variances; it can be adaptively used to consider the significance of compared temporal fingerprints. The experimental results show that the proposed modality fusion method outperforms other state-of-the-arts fusion methods and popular spatio-temporal fingerprints in terms of video copy detection. Furthermore, the proposed method can save 39.0%, 25.1%, and 46.1% time complexities needed to perform video fingerprint matching without a significant loss of detection accuracy for our synthetic dataset, TRECVID 2009 CCD Task, and MUSCLE-VCD 2007, respectively. This result indicates that our proposed method can be readily incorporated into the real-life video copy detection systems.     

Rotation and flipping robust region binary patterns for video copy detection

Many video fingerprints have been proposed to handle the video transformations problems when the original contents are copied and redistributed. However, most of them did not take into account flipping and rotation transformations. In this paper, we propose a novel video fingerprint based on region binary patterns, aiming to realize robust and fast video copy detection against video transformations including rotation and flipping. We extract two complementary region binary patterns from several rings in keyframes. These two kinds of binary patterns are converted into a new type of patterns for the proposed video fingerprint which is robust against rotation and flipping. The experimental results demonstrated that the proposed video fingerprint is effective for video copy detection particularly in the case of rotation and flipping. Furthermore, our experimental results proved that the proposed method allows for high storage efficiency and low computation complexity, which is suitable for practical video copy system.     

一种基于二分图最优匹配的镜头检索方法

镜头检索是基于内容的视频检索的重要内容.本文首次尝试将二分图的最优匹配用于镜头检索.与现有方法相比,本文提出的方法强调在一一对应的前提下,全面客观地度量两个镜头的相似度.把两个镜头的相似度度量建模为一个带权的二分图:镜头中的每一帧看成二分图的一个结点,两个镜头之间任意帧的相似值作为边的权值.在一一对应的前提下,利用最优匹配的Kuhn-Munkres算法求出该二分图的最大权,以此作为两个镜头的相似度.考虑到检索速度问题,提出了两个改进算法.实验对比结果证实了本文所提方法在镜头检索中的优异表现.     

Video key frame extraction through dynamic Delaunay clustering with a structural constraint

Key frame based video summarization has emerged as an important area of research for the multimedia community. Video key frames enable an user to access any video in a friendly and meaningful way. In this paper, we propose an automated method of video key frame extraction using dynamic Delaunay graph clustering via an iterative edge pruning strategy. A structural constraint in form of a lower limit on the deviation ratio of the graph vertices further improves the video summary. We also employ an information-theoretic pre-sampling where significant valleys in the mutual information profile of the successive frames in a video are used to capture more informative frames. Various video key frame visualization techniques for efficient video browsing and navigation purposes are incorporated. A comprehensive evaluation on 100 videos from the Open Video and YouTube databases using both objective and subjective measures demonstrate the superiority of our key frame extraction method.     

基于内容复杂度的视频编码码率控制

该文根据线性模型提出信源内容复杂度的一种度量方式,并以此进行帧级比特分配和宏块级的视频码率控制。仿真表明该方法与MPEG2中的TM5相比,能比较显著地提高信噪比,实现更加准确的码率控制,同时可以在帧间和帧内获得更一致的视觉效果。该算法在MPEG4及低码率视频编码中也是适用的。     

Stereo object tracking with fusion of texture,color and disparity information

A novel method for visual object tracking in stereo videos is proposed, which fuses an appearance based representation of the object based on Local Steering Kernel features and 2D color–disparity histogram information. The algorithm employs Kalman filtering for object position prediction and a sampling technique for selecting the candidate object regions of interest in the left and right channels. Disparity information is exploited, for matching corresponding regions in the left and right video frames. As tracking evolves, any significant changes in object appearance due to scale, rotation, or deformation are identified and embodied in the object model. The object appearance changes are identified simultaneously in the left and right channel video frames, ensuring correct 3D representation of the resulting bounding box in a 3D display monitor. The proposed framework performs stereo object tracking and it is suitable for application in 3D movies, 3D TV content and 3D video content captured by consuming stereo cameras. Experimental results proved the effectiveness of the proposed method in tracking objects under geometrical transformations, zooming and partial occlusion, as well as in tracking slowly deforming articulated 3D objects in stereo video.     

Gradient Fusion Method for Night Video Enhancement

To resolve video enhancement problems, a novel method of gradient domain fusion wherein gradient domain frames of the background in daytime video are fused with nighttime video frames is proposed. To verify the superiority of the proposed method, it is compared to conventional techniques. The implemented output of our method is shown to offer enhanced visual quality.     

A heuristic for the retrieval of objects in video in the framework of the rough indexing paradigm

In this paper, we tackle the problem of matching of objects in video in the framework of the rough indexing paradigm. In this context, the video data are of very low spatial and temporal resolution because they come from partially decoded MPEG compressed streams. This paradigm enables us to achieve our purpose in near real time due to the faster computation on rough data than on original full spatial and temporal resolution video frames.In this context, segmentation of rough video frames is inaccurate and the region features (texture, color, shape) are not strongly relevant. The structure of the objects must be considered in order to improve the robustness of the matching of regions. The problem of object matching can be expressed in terms of region adjacency graph (RAG) matching.Here, we propose a directed acyclic graph (DAG) matching method based on a heuristic in order to approximate object matching. The RAGs to compare are first transformed into DAGs by orienting edges. Then, we compute some combinatoric metrics on nodes in order to classify them by similarity. At the end, a top-down process on DAGs aims to match similar patterns that exist between the two DAGs.The results are compared with those of a method based on relaxation matching.     

A Frame‐Based Video Signature Method for Very Quick Video Identification and Location

A video signature is a set of feature vectors that compactly represents and uniquely characterizes one video clip from another for fast matching. To find a short duplicated region, the video signature must be robust against common video modifications and have a high discriminability. The matching method must be fast and be successful at finding locations. In this paper, a frame‐based video signature that uses the spatial information and a two‐stage matching method is presented. The proposed method is pair‐wise independent and is robust against common video modifications. The proposed two‐stage matching method is fast and works very well in finding locations. In addition, the proposed matching structure and strategy can distinguish a case in which a part of the query video matches a part of the target video. The proposed method is verified using video modified by the VCE7 experimental conditions found in MPEG‐7. The proposed video signature method achieves a robustness of 88.7% under an independence condition of 5 parts per million with over 1,000 clips being matched per second.     

基于带权值无向图的视频隐写分析

针对视频帧的时域特性,提出一种以帧间相关性构建带权值无向图的视频隐写分析方法。首先,分别计算待检测视频每帧亮度的灰度共生矩阵,把得出的8维特征作为该帧的特征向量。再以视频帧为节点,用帧间特征向量的欧氏距离作为节点间的权值,构造出表示帧间相关性的带权值无向图。根据嵌入信息后帧间相关性发生改变的特性来判断视频中是否有秘密信息嵌入。实验结果表明,用带权值无向图的方法可以快速准确地区分载密视频和原始视频,并且有较高的正确率。     

Contour detection of the left ventricular cavity from angiographic images

A knowledge-based heuristic method is proposed to outline the left ventricular cavity from end-diastolic angiographic images in right anterior oblique projection in man. The algorithm search for the optimal path in a weighted graph, representing the state space, can implicitly be defined as the set of all the contour segments that can be produced by successor operators. Applications to routine images are presented.     

基于压缩感知和熵计算的关键帧提取算法

针对关键帧提取问题,提出了一种基于压缩感知理 论和熵计算的关键帧提取算法, 首先通过构造符合有限等距性质要求的稀疏随机投影矩阵,将高维多尺度帧图像特征变换为 低维多尺度帧图像特征, 并形成视频镜头低维多尺度特征列向量组;然后通过随机权值向量与低维多尺度特征向量的 阿达玛乘积运算生成各 帧图像的匹配特征,并根据匹配特征的相似性度量完成镜头内部的子镜头分割;最后通过交 叉熵计算在每个子镜头 中得到可能的关键帧,并由图像熵计算确定最终的关键帧。实验表明,与传统方法相比,本 文算法提取的关键帧能够更精确、更稳定描述视频镜头内容。     

基于组合相似性的视频检索

该文研究基于镜头的视频检索问题,提出了一种新的基于组合相似性的镜头相似性度量方法。首先把镜头看成由帧序列组成的一个组合,镜头的相似性通过帧组合的相似性来度量。其次通过用一个非线性映射,把帧组合所在的空间映射到一个高维空间,在这个空间中,假设帧组合服从正态分布,利用核方法,抽取出关键帧序列,并计算出两个正态分布之间的概率距离,这个距离表明了帧组合的相似程度,从而得到两个镜头之间的相似性。最后将这种方法应用于基于镜头的视频检索中,实验表明在相同条件下,基于该方法的检索效果明显优于传统的欧式距离和直方图交方法。     

基于位平面匹配和卡尔曼滤波的视频稳定

针对数字视频帧间平移抖动的稳定问题,介绍一种基于局部求精位平面匹配运动估计和约束卡尔曼滤波运动校正的视频稳定算法。运动估计首先结合了灰阶比特平面匹配和菱形搜索策略得到初步的估计结果,然后在其附近再以最小绝对差（MAD）为测度,搜索更为准确的运动估计结果。这种运动估计方法在保证估计精度的前提下,显著地减少了运动估计需要的计算量。运动校正则考虑到实际稳像系统对校正量可能存在的某些约束,对绝对帧位移曲线采用约束卡尔曼滤波,得到平滑的位移曲线,有效地降低了帧间抖动的幅度,同时保证了校正矢量不超过稳像系统的实际校正能力。仿真实验表明,该算法具有精度高、速度快的特点,尤其适用于实时视频稳定。     

A practical design of digital watermarking for video streaming services

A practical design of digital watermarking for video streaming services is proposed in this research. The information of a legitimate recipient is represented as a watermark, which is embedded in the video stream to serve as a cue to trace the recipient in case a clone of the video is illegally distributed. The watermark signals are designed to embed in some areas of video frames to benefit the video stream server, as the result of only partial actions required, including decoding, processing and re-encoding. The invariance of feature points and the self-similarity of hidden signals are further exploited to enable watermark detection without involving the original video. The watermark can decently survive transcoding processes and geometrical modifications of frames. The experimental results demonstrate the advantages of the proposed scheme in terms of watermark visibility, capacity and detection methodology.     

基于关键帧颜色和纹理特征的视频拷贝检测

提出了一种基于关键帧颜色和纹理特征的视频拷贝检测方法。首先通过子片段方法提取视频的关键帧,然后将关键帧分成3个子块,提取每个子块的三维量化颜色直方图,通过直方图相交法来进行颜色特征的匹配。对检索得到的结果视频关键帧进行纹理特征提取,通过其灰度共生矩阵的角二阶矩和熵来表征其纹理特征,纹理特征的匹配可进一步过滤不相关的视频。实验结果表明,该方法效果好、稳健性强且可应用于多种类型的视频。