Quasi-commutative watermarking and encryption for secure media content distribution

Commutative Watermarking and Encryption (CWE) provides a solution for interoperation between watermarking and encryption. It realizes the challenging operation that embeds a watermark into the encrypted multimedia data directly, which avoids the decryption–watermarking–encryption triples. Till now, few CWE schemes have been reported. They often obtain the commutative property by partitioning multimedia data into independent parts (i.e., the encryption part and the watermarking part). Since the two parts are isolated, it can not keep secure enough against replacement attacks. To avoid the disadvantage, a novel quasi-commutative watermarking and encryption (QCWE) scheme based on quasi-commutative operations is proposed in this paper. In the proposed scheme, the encryption operation and watermarking operation are applied to the same data part. Since the two operations are homogenous with commutative properties, their orders can be commutated. As an example, the scheme for MPEG2 video encryption and watermarking is presented. In this example, the DCs in intra macroblocks are encrypted or watermarked based on random module addition, while the DCs in other macroblocks and all the ACs’ signs are encrypted with a stream cipher or block cipher. Analysis and experiments show that the scheme obtains high perceptual security and time efficiency, and the watermarking and encryption operations can be commutated. These properties make the scheme a suitable choice for efficient media content distribution. Additionally, the paper shows the availability of constructing the commutative watermarking and encryption scheme with homogenous operations, which is expected to activate the new research topic.

A scalable signature scheme for video authentication

This paper addresses the problem of ensuring the integrity of a digital video and presents a scalable signature scheme for video authentication based on cryptographic secret sharing. The proposed method detects spatial cropping and temporal jittering in a video, yet is robust against frame dropping in the streaming video scenario. In our scheme, the authentication signature is compact and independent of the size of the video. Given a video, we identify the key frames based on differential energy between the frames. Considering video frames as shares, we compute the corresponding secret at three hierarchical levels. The master secret is used as digital signature to authenticate the video. The proposed signature scheme is scalable to three hierarchical levels of signature computation based on the needs of different scenarios. We provide extensive experimental results to show the utility of our technique in three different scenarios—streaming video, video identification and face tampering.

A framework for a video analysis tool for suspicious event detection

This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent surveillance video. Ideas and techniques for closing the semantic gap between low-level machine readable features of video data and high-level events seen by a human observer are discussed. An evaluation of the event classification and detection technique is presented and a future experiment to refine this technique is proposed. These experiments are used as a lead to a discussion on the most optimal machine learning algorithm to learn the event representation scheme proposed in this paper.

Real-time 2D to 3D video conversion

We present a real-time implementation of 2D to 3D video conversion using compressed video. In our method, compressed 2D video is analyzed by extracting motion vectors. Using the motion vector maps, depth maps are built for each frame and the frames are segmented to provide object-wise depth ordering. These data are then used to synthesize stereo pairs. 3D video synthesized in this fashion can be viewed using any stereoscopic display. In our implementation, anaglyph projection was selected as the 3D visualization method, because it is mostly suited to standard displays.

EPCRTT-based smoothing and multiplexing of VBR video traffic

Applying video smoothing techniques to real-time video transmission can significantly reduce the peak rate and rate variability of compressed video streams. Moreover, statistical multiplexing of the smoothed traffic can substantially improve network utilization. In this paper we propose a new smoothing scheme, which exploits statistical multiplexing gain that can be obtained after smoothing of individual video streams. We present a new bandwidth allocation algorithm that allows for responsive interactivity. The local re-smoothing algorithm is carried out using an iterative process. In the proposed scheme the smoothed video streams are divided into fixed intervals and then a new transmission schedule for each interval is calculated. The problem of applying an optimal transmission schedule for aggregated smoothing video streams is shown to be NP-hard problem. Partitioning the whole stream into sections enables parallel processing of the smoothing algorithm in real-time before transmission. This approach allows partial transmission of the multiplexed stream while smoothing other intervals. The simulation results show a significant reduction in peak rate and rate variability of the aggregated stream, compared to the non-smoothing case. Therefore the proposed scheme allows us to increase the number of simultanusally-served video streams.

Adaptive training of video sets for image recognition on mobile phones

We present an enhancement towards adaptive video training for PhoneGuide, a digital museum guidance system for ordinary camera-equipped mobile phones. It enables museum visitors to identify exhibits by capturing photos of them. In this article, a combined solution of object recognition and pervasive tracking is extended to a client–server-system for improving data acquisition and for supporting scale-invariant object recognition. A static as well as a dynamic training technique are presented that preprocess the collected object data differently and apply two types of neural networks (NN) for classification. Furthermore, the system enables a temporal adaptation for ensuring a continuous data acquisition to improve the recognition rate over time. A formal field experiment reveals current recognition rates and indicates the practicability of both methods under realistic conditions in a museum.

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Real time video frames allocation in mobile networks using cooperative pre-fetching

In this paper, we study the bandwidth allocation problem for serving video requests in a mobile real-time video player system. One of the main issues to maintain the quality of services (QoS) in mobile video playback is to ensure sufficient number of video frames available at the client side while a video is being played. However, due to the limited bandwidth of a mobile network and variable workload streaming video, this is not easy to achieve in practice. In addition, the communication link between mobile clients and a video server is subject to frequent errors and temporary disconnection. In this paper, we propose to use the notion of buffered bandwidth in addition to the network bandwidth to support real-time playback of videos at mobile clients. Based on this, we designed a bandwidth allocation scheme called Cooperative Pre-Fetching (CP) in which the amount of bandwidth to be allocated to serve a video request depends on the current buffer level of the video at the client relative to the target buffer level of the client. In determining the target buffer level, we consider the errors in communication to the client as well as the other clients who are concurrently served by the system. The buffered video frames at the clients are then used to minimize the impact of error in communications on the overall QoS of video playbacks in the whole system.

Detecting repeats for video structuring

Television daily produces massive amounts of videos. Digital video is unfortunately an unstructured document in which it is very difficult to find any information. Television streams have however a strong and stable but hidden structure that we want to discover by detecting repeating objects in the video stream. This paper shows that television streams are actually highly redundant and that detecting repeats can be an effective way to detect the underlying structure of the video. A method for detecting these repetitions is presented here with an emphasis on the efficiency of the search in a large video corpus. Very good results are obtained both in terms of effectiveness (98% in recall and precision) as well as efficiency since one day of video is queried against a 3 weeks dataset in only 1 s.

Transmission of layered video streaming via multi-path on ad hoc networks

Mobile ad hoc networks without centralized infrastructure change their topology rapidly because of node mobility, making multimedia applications difficult to run across wireless networks. Moreover, video transmission over ad hoc networks causes frequent transmission loss of video packets owing to end-to-end transmission with a number of wireless links, and requires essential bandwidth and restricted delay to provide quality-guaranteed display. This paper presents an architecture supporting transmission of multiple video streams in ad hoc networks by establishing multiple routing paths to provide extra video coding and transport schemes. This study also proposes an on-demand multicast routing protocol to transport layered video streams. The multicast routing protocol transmits layered video streaming based on a weight criterion, which is derived according to the number of receivers, delay and expiration time of a route. A simulation is performed herein to indicate the viability and performance of the proposed approach. The simulation results demonstrate that the proposed transport scheme is more effective than other video transport schemes with single or multiple paths.

A secure e-auction scheme based on group signatures

Recently, electronic auctions have been receiving more and more attention in the world of electronic commerce. The security and efficiency of electronic auctions are becoming important. We shall propose a securely sealed-bid auction scheme that uses our group signature scheme with the function of authenticated encryption. It can achieve the following goals: secrecy of bidding price, anonymity, verifiability, non-repudiation, and better performance.

Dynamic video summarization using two-level redundancy detection

The mushroom growth of video information, consequently, necessitates the progress of content-based video analysis techniques. Video summarization, aiming to provide a short video summary of the original video document, has drawn much attention these years. In this paper, we propose an algorithm for video summarization with a two-level redundancy detection procedure. By video segmentation and cast indexing, the algorithm first constructs story boards to let users know main scenes and cast (when this is a video with cast) in the video. Then it removes redundant video content using hierarchical agglomerative clustering in the key frame level. The impact factors of scenes and key frames are defined, and parts of key frames are selected to generate the initial video summary. Finally, a repetitive frame segment detection procedure is designed to remove redundant information in the initial video summary. Results of experimental applications on TV series, movies and cartoons are given to illustrate the proposed algorithm.

A survey on peer-to-peer video streaming systems

Video-over-IP applications have recently attracted a large number of users on the Internet. Traditional client-server based video streaming solutions incur expensive bandwidth provision cost on the server. Peer-to-Peer (P2P) networking is a new paradigm to build distributed network applications. Recently, several P2P streaming systems have been deployed to provide live and on-demand video streaming services on the Internet at low server cost. In this paper, we provide a survey on the existing P2P solutions for live and on-demand video streaming. Representative P2P streaming systems, including tree, multi-tree and mesh based systems are introduced. We describe the challenges and solutions of providing live and on-demand video streaming in P2P environment. Open research issues on P2P video streaming are also discussed.

Evaluation and monitoring of video quality for UMA enabled video streaming systems

This paper deals with monitoring user perception of multimedia presentations in a Universal Multimedia Access (UMA) enabled system using objective no-reference (NR) metrics. These NR metrics are designed for an UMA-enabled system, in a novel architecture, for a multimedia viewer. The first metric measures block-edge impairments in a video frame at the receiver end, based on the observation that they occur in regions with low spatial activity. The second metric evaluates the quality of the reconstructed video frame in the event of packet loss. Here, the structure of the artifact is itself exploited for the evaluation. Both the metrics involve low computational complexity and are feasible for real-time monitoring of streaming video in a multimedia communication scenario. Further, in rate-adaptive streaming of video, these metrics could serve as feedback parameters to dynamically adapt the bit rates based on network congestion.

Structure and event mining in sports video with efficient mosaic

Video is an information-intensive media with much redundancy. Therefore, it is desirable to be able to mine structure or semantics of video data for efficient browsing, summarization and highlight extraction. In this paper, we propose a mosaic based approach to key-event as well as structure mining, which is regarded as a complementary view for sports video analysis. Mosaic is generated for each shot by a novel efficient mosaicing scheme, which constructs a global motion path and selects a best subset of frames for mosaicing. These improved mosaics are then used as the representative image of shot content. Based on mosaic, the structure and event in sports video are mined by the methods with prior knowledge and without prior knowledge. Without prior knowledge, our system is able to locate global view shots taken by dominant camera. If prior knowledge is available, the events in these global view shots are detected using robust features extracted from mosaics. For global view mining, the experiments compared with key-frame-based scheme have demonstrated that this mosaic-based scheme presents better results in several kinds of sports videos; for events mining, the detection of key-plays and key-events in the specific-domain of soccer videos have proved its effectiveness.

OCS: An effective caching scheme for video streaming on overlay networks

Video streaming is vital for many important applications such as distance learning, digital video libraries, and movie-on-demand. Since video streaming requires significant server and networking resources, caching has been used to reduce the demand on these resources. In this paper, we propose a novel collaboration scheme for video caching on overlay networks, called Overlay Caching Scheme (OCS), to further minimize service delays and loads placed on an overlay network for video streaming applications. OCS is not a centralized nor a hierarchical collaborative scheme. Despite its design simplicity, OCS effectively uses an aggregate storage space and capability of distributed overlay nodes to cache popular videos and serve nearby clients. Moreover, OCS is light-weight and adaptive to clients’ locations and request patterns. We also investigate other video caching techniques for overlay networks including both collaborative and non-collaborative ones. Compared with these techniques on topologies inspired from actual networks, OCS offers extremely low average service delays and approximately half the server load. OCS also offers smaller network load in most cases in our study.

Optimized scalable cache management for video streaming system

An important research issue in video streaming is how to efficiently utilize the network resources to provide clients instant access to multiple video objects. Caching strategy and transmission scheme are the two essential points inside the video streaming framework. Recent research efforts on them are not sufficient due to their inflexible support for scalable encoded video streams and heterogeneous requests from clients. In this paper, we propose an optimized caching strategy (OCS) and a scalable transmission scheme (STS) for scalable coded video streaming. By exploring the characteristics of video streaming workload and system design objectives, OCS and STS work efficiently to minimize both network bandwidth cost and user access latency. Firstly, we analyze the caching problem for the proxy-assisted video streaming system and derive a maneuverable caching scenario. Secondly, we develop an efficient transmission scheme for scalable coded videos. Thirdly, we formulate a multi-objective optimization model with closed-form expressions to obtain the optimized caching strategy. Finally, with designed algorithms, an excellent compromise between two competing objectives (minimizing the bandwidth cost and the access latency) is achieved. We start our evaluation by studying the optimized caching strategy for a single video object. Then we apply the strategy to multiple video objects and illustrate the tradeoff between the optimization objectives. Our evaluation results show that compared with other caching strategies, the proposed optimized scalable caching strategy can achieve a significant reduction in bandwidth cost with even a small proxy cache size. Meanwhile, the best performance (in terms of bandwidth cost) is obtained together with the proposed scalable batch-patching transmission scheme.

Distributed video coding based on part intracoding and soft side information estimation

Recently, distributed source coding (DSC) has been proposed to implement source compression by exploiting source statistics at the decoder only, which enables low-complexity video coding. However, to date, the video codecs based on DSC have been unable to compress as efficiently as traditional predictive video codecs, such as H.264. So, new techniques have to be investigated to improve the performance of the distributed video coding scheme for practical applications. In this paper, I propose a novel distributed video coding scheme based on part intracoding and soft side information estimation. Firstly, at the encoder side, to improve the compression performance of distributed video coding system, we divide the video data into strongly correlative data encoded by Slepian–Wolf codec and weakly correlative data encoded by Intracoding codec. Secondly, at the decoder side, to improve the accuracy of side information estimation, a soft side information estimation method is proposed, which is more suitable for video coding due to the non-stationary feature of video data. Our experimental results show that the performance of our coding system is better than that of the traditional distributed video coding system while keeping the simple encoding property. Also the concept of soft side information is a new idea in distributed video coding and will significantly influence the side information estimation method.

Video protection for MPEG-4 FGS with watermarking

The MPEG-4 fine granularity scalability (FGS) video coding standard offers flexible adaptation to varying network bandwidths and different application needs. This paper presents a MPEG-4 FGS video CODEC based watermarking scheme to embed watermark during encoding. Watermark is embedded into base layer, and can be extracted from both base layer and enhanced video through eliminating the influence of enhancement layer on watermark. This scheme eliminates error propagation caused by watermark for normal video, and utilizes error propagation caused by watermark adjustment to protect the video content. This scheme provides dual protection for intellectual property rights (IPR): watermark and video content protection utilizing error propagation in temporal motion compensation prediction. Watermark is embedded into I-VOP, and is adjusted before I-VOP is reconstructed as reference VOP. Only customers with authorization can adjust the watermark correctly during decoding to get good video quality. Illegal customers can also access the video, but with bad quality. This scheme has the virtue of providing dual protection with a little expense. Theoretical bounds of watermark embedding strength to keep watermark invisibility and of watermark adjustment strength to get enough protective effect are calculated. Some experimental results are given and analyzed.

Real-time stabilization of long range observation system turbulent video

The paper presents a real-time algorithm that compensates image distortions due to atmospheric turbulence in video sequences, while keeping the real moving objects in the video unharmed. The algorithm involves (1) generation of a “reference” frame, (2) estimation, for each incoming video frame, of a local image displacement map with respect to the reference frame, (3) segmentation of the displacement map into two classes: stationary and moving objects; (4) turbulence compensation of stationary objects. Experiments with both simulated and real-life sequences have shown that the restored videos, generated in real-time using standard computer hardware, exhibit excellent stability for stationary objects while retaining real motion.

Combining graph connectivity &; dominant set clustering for video summarization

The paper presents an automatic video summarization technique based on graph theory methodology and the dominant sets clustering algorithm. The large size of the video data set is handled by exploiting the connectivity information of prototype frames that are extracted from a down-sampled version of the original video sequence. The connectivity information for the prototypes which is obtained from the whole set of data improves video representation and reveals its structure. Automatic selection of the optimal number of clusters and hereafter keyframes is accomplished at a next step through the dominant set clustering algorithm. The method is free of user-specified modeling parameters and is evaluated in terms of several metrics that quantify its content representational ability. Comparison of the proposed summarization technique to the Open Video storyboard, the Adaptive clustering algorithm and the Delaunay clustering approach, is provided.