Data hiding techniques are usually applied into digital watermarking or digital fingerprinting, which is used to protect intellectual property rights or to avoid illegal copies of the original works. It has been pointed out that data hiding can be utilized as a communication medium. In conventional digital watermarking frameworks, it is required that the difference between the cover objects and the stego objects are quite small, such that the difference cannot be recognized by human sensory systems. On the other hand, the authors have proposed a ‘hearable’ data hiding technique for audio signals that can carry secret messages and can be naturally recognized as a musical piece by human ears. In this study, we extend the idea of the hearable data hiding into video signals by utilizing the visual effects. As visual effects, we employ fade-in and fade-out effects which can be used as a kind of visual rendering for scene transitions. In the proposed schemes, secret messages are generated as one-dimensional barcodes which are used for fade-in or fade-out effects. The present paper shows that the proposed schemes have the high accuracy in extracting the embedded messages even from the video signals captured by smartphones or tablets. It is also shown that the video signals conveying the embedded messages can be naturally recognized by human visual systems through subjective evaluation experiments.

The topic of retrieving videos containing a desired person from a dataset just using the content of faces without any help of textual information has many interesting applications like video surveillance, social network, video mining, etc. However, traditional face matching against a huge number of detected faces leads to an unacceptable response time and may also reduce the accuracy due to the large variations in facial expressions, poses, lighting, etc. Therefore, in this paper we propose a novel method to generate discriminative “signatures” for efficiently retrieving the videos containing the same person with a query. In this research, the signature is defined as a compact, discriminative and reduced dimensionality representation, which is generated from a set of high-dimensional feature vectors of an individual. The desired videos are retrieved based on the similarities between the signature of the query and those of individuals in the database. In particular, we make the following contributions. Firstly, we give an algorithm of two directional linear discriminant analysis with maximum correntropy criterion (2DLDA-MCC) as an extension to our recently proposed maximum correntropy criterion based linear discriminant analysis (LDA-MCC). Both algorithms are robust to outliers and noise. Secondly, we present an approach for transferring a set of exemplars to a fixed-length signature using LDA-MCC and 2DLDA-MCC, resulting in two kinds of signatures that are called 1D signature and 2D signature. Finally, a novel video retrieval scheme is given based on the signatures, which has low storage requirement and can achieve a fast search. Evaluations on a large dataset of videos show reliable measurement of similarities by using the proposed signatures to represent the identities generated from videos. Experimental results also demonstrate that the proposed video retrieval scheme has the potential to substantially reduce the response time and slightly increase the mean average precision of retrieval.

We are interested in retrieving video shots or videos containing particular people from a video dataset. Owing to the large variations in pose, illumination conditions, occlusions, hairstyles and facial expressions, face tracks have recently been researched in the fields of face recognition, face retrieval and name labeling from videos. However, when the number of face tracks is very large, conventional methods, which match all or some pairs of faces in face tracks, will not be effective. Therefore, in this paper, an efficient method for finding a given person from a video dataset is presented. In our study, in according to performing research on face tracks in a single video, we also consider how to organize all the faces in videos in a dataset and how to improve the search quality in the query process. Different videos may include the same person; thus, the management of individuals in different videos will be useful for their retrieval. The proposed method includes the following three points. (i) Face tracks of the same person appearing for a period in each video are first connected on the basis of scene information with a time constriction, then all the people in one video are organized by a proposed hierarchical clustering method. (ii) After obtaining the organizational structure of all the people in one video, the people are organized into an upper layer by affinity propagation. (iii) Finally, in the process of querying, a remeasuring method based on the index structure of videos is performed to improve the retrieval accuracy. We also build a video dataset that contains six types of videos: films, TV shows, educational videos, interviews, press conferences and domestic activities. The formation of face tracks in the six types of videos is first researched, then experiments are performed on this video dataset containing more than 1 million faces and 218,786 face tracks. The results show that the proposed approach has high search quality and a short search time.

This paper presents a method for lossy compression of digital video data by parametric line and Natural cubic spline approximation. The method estimates the variation of pixel values in the temporal dimension by taking group of pixels together as keyblocks and interpolating them in Euclidean space. Break and fit criterion is used to minimize the number of keyblocks required for encoding and decoding of approximated data. Each group of pixels at fixed spatial location is encoded/decoded independently. The proposed method can easily be incorporated in the existing video data compression techniques based on Discrete Cosine Transform or Wavelet Transform.

With the advent of digital video and digital broadcasting, copyright protection of video data has been one of the most important issues. We present in this paper a novel method of digital watermark for video data based on the discrete wavelet transform. In this method, we embed the watermark in the lowest frequency components of each frame in the uncoded video by using a controlled quantization process. The watermark can be extracted directly from the decoded video without access to the original video. Experimental results show that the proposed method gives the watermarked image of better quality and is robust against MPEG coding and re-encoding. Furthermore, we discuss multiple watermarking with regard to the generational copy control for video contents.

This paper surveys recent research activities on three major areas of digital media information base, namely, video database systems as a typical example of temporal application, database systems for mixed reality as an instance of spatial application, and kansei management for digital media retrieval as a case of humanistic feelings application. Current research results by the project Advanced Database Systems for Integration of Media and User Environments are reported.

This paper focuses on the problems how to organize and retrieve video data in an effective manner. First we identify several issues to be solved for the problems. Next, we overview our current research results together with a brief survey in the research area of video databases. We especially describe the following research results obtained by the the Japanese Ministry of Education under Grant-in-Aid for Scientific Research on Priority Area: "Advanced Databases" concerned with organization and retrieval of video data: Instance-Based Video Annotation Models, Self-Organization of Video Data, and A Query Model for Fragmentally Indexed Video.

Discussed here is progress achieved in the development of video codec LSIs.First, the amount of computation for various standards, and signal handling capability (throughput) and power dissipation for video codec LSIs are described. Then, general technologies for improving throughtput are briefly summarized. The paper also reviews three approaches (i.e., video signal processor, building block and monolithic codes) for implementing video codes standards. The second half of the paper discusses various high-throughput technologies developed for programmable Video Signal Processor (VSP) LSIs. A number of VSP LSIs are introduced, including the world's first programmable VSP, developed in February 1987 and a monolithic codec ship, built in February 1993 that is sufficient in itself for the construction of a video encoder for encoding full-CIF data at 30 frames per second. Technologies for reduction of power dissipation while keeping maintaining throughput are also discussed.

This papaer presents a data model and the database system architecture to handle multimedia data, especially video (or image sequence) data. A new scheme AIS diagram" is introduced, by which all informations about entities and relationships among bitmap frames or textual informations are described in a uniform way. We focus on the integration of engineering data. The most important problem to be solved is how to capture the objects" in each frame and to represent them in the data model. For this purpose we propose physical cut" and logical cut" as a unit of information in image sequences and, using those concepts, we developed a prototype system for multimedia data processing on a conventional database system.