This paper introduces our work on a Movie Map, which will enable users to explore a given city area using 360° videos. Visual exploration of a city is always needed. Nowadays, we are familiar with Google Street View (GSV) that is an interactive visual map. Despite the wide use of GSV, it provides sparse images of streets, which often confuses users and lowers user satisfaction. Forty years ago, a video-based interactive map was created - it is well-known as Aspen Movie Map. Movie Map uses videos instead of sparse images and seems to improve the user experience dramatically. However, Aspen Movie Map was based on analog technology with a huge effort and never built again. Thus, we renovate the Movie Map using state-of-the-art technology. We build a new Movie Map system with an interface for exploring cities. The system consists of four stages; acquisition, analysis, management, and interaction. After acquiring 360° videos along streets in target areas, the analysis of videos is almost automatic. Frames of the video are localized on the map, intersections are detected, and videos are segmented. Turning views at intersections are synthesized. By connecting the video segments following the specified movement in an area, we can watch a walking view along a street. The interface allows for easy exploration of a target area. It can also show virtual billboards in the view.

We can enjoy various video contents such as movies in several ways. In this report, we show the effects of content differences on physiological parameters such as eye movements and CFF. This time we confirmed the difference in responses that after watching a movie. In addition, a consistent change that can infer that due to a movie was also indicated. Our results showed that content differences affect the parameters. This suggests the possibility that the influence of movie contents on the viewer can be evaluated by physiological parameters.

In many movies, social conditions and awareness of the issues of the times are depicted in any form. Even if fantasy and science fiction are works far from reality, the character relationship does mirror the real world. Therefore, we try to understand social conditions of the real world by analyzing the movie. As a way to analyze the movies, we propose a method of estimating interpersonal relationships of the characters, using a machine learning technique called Markov Logic Network (MLN) from movie script databases on the Web. The MLN is a probabilistic logic network that can describe the relationships between characters, which are not necessarily satisfied on every line. In experiments, we confirmed that our proposed method can estimate favors between the characters in a movie with F-measure of 58.7%. Finally, by comparing the relationships with social indicators, we discussed the relevance of the movies to the real world.

In this paper, we introduce layered low-density generator matrix (Layered-LDGM) codes for super high definition (SHD) scalable video systems. The layered-LDGM codes maintain the correspondence relationship of each layer from the encoder side to the decoder side. This resulting structure supports partial decoding. Furthermore, the proposed layered-LDGM codes create highly efficient forward error correcting (FEC) data by considering the relationship between each scalable component. Therefore, the proposed layered-LDGM codes raise the probability of restoring the important components. Simulations show that the proposed layered-LDGM codes offer better error resiliency than the existing method which creates FEC data for each scalable component independently. The proposed layered-LDGM codes support partial decoding and raise the probability of restoring the base component. These characteristics are very suitable for scalable video coding systems.

"Dive into the Movie (DIM)" is a name of project to aim to realize a world innovative entertainment system which can provide an immersion experience into the story by giving a chance to audience to share an impression with his family or friends by watching a movie in which all audience can participate in the story as movie casts. To realize this system, several techniques to model and capture the personal characteristics instantly in face, body, gesture, hair and voice by combining computer graphics, computer vision and speech signal processing technique. Anyway, all of the modeling, casting, character synthesis, rendering and compositing processes have to be performed on real-time without any operator. In this paper, first a novel entertainment system, Future Cast System (FCS), is introduced which can create DIM movie with audience's participation by replacing the original roles' face in a pre-created CG movie with audiences' own highly realistic 3D CG faces. Then the effects of DIM movie on audience experience are evaluated subjectively. The result suggests that most of the participants are seeking for higher realism, impression and satisfaction by replacing not only face part but also body, hair and voice. The first experimental trial demonstration of FCS was performed at the Mitsui-Toshiba pavilion of the 2005 World Exposition in Aichi Japan. Then, 1,640,000 people have experienced this event during 6 months of exhibition and FCS became one of the most popular events at Expo.2005.

Effective classification and analysis of semantic contents are very important for the content-based indexing and retrieval of video database. Our research attempts to classify movie clips into three groups of commonly elicited emotions, namely excitement, joy and sadness, based on a set of abstract-level semantic features extracted from the film sequence. In particular, these features consist of six visual and audio measures grounded on the artistic film theories. A unique sieving-structured neural network is proposed to be the classifying model due to its robustness. The performance of the proposed model is tested with 101 movie clips excerpted from 24 award-winning and well-known Hollywood feature films. The experimental result of 97.8% correct classification rate, measured against the collected human-judges, indicates the great potential of using abstract-level semantic features as an engineered tool for the application of video-content retrieval/indexing.

Under the broadband-ubiquitous environment, digital content creation/distribution will be the key factor to activating new industries. This paper first describes the impact of a broadband-ubiquitous environment on digital content creation/distribution; then it proposes new models for digital content creation/distribution businesses. In a broadband-ubiquitous environment, the key is creation of moving picture content; thus the paper describes a system that allows non-CG experts to make CG movies easily.

In virtue of great progress in computer graphics technologies, CG movies have been getting popular. However, cinematography techniques, which contribute to improving the contents' comprehensibility, need to be learned from professional experiences, and not easily acquired by non-professional people. This paper focuses on film cutting as one of the most important cinematography techniques in conversational scenes, and presents a system that automatically generates shot transitions to improve comprehensibility of CG contents. First, we propose a cognitive model of User Involvement serving as constraints on selecting shot transitions. Then, to examine the validity of the model, we analyze shot transitions in TV programs, and based on the analysis, we implement a CG contents creation system. Results of our preliminary evaluation experiment show the effectiveness of the proposed method, specifically in enhancing contents' comprehensibility.

In this paper, we first investigate the characteristics of movie contents over the Internet. As in the previous studies, we found the lognormal-distribution well fits the distribution of file size for the whole set of general movie contents. When we specifically focus on the subset that consists of movie trailers, however, it shows different distribution from the lognormal-distribution. Our analysis shows it is similar to an exponential-distribution. We here assume that movie trailers are one of the relevant contents for Contents Delivery Networks (CDN) or Peer-to-Peer (P2P) file exchange communities. We further studies the relationship between playing duration and file size for the movie trailers and we did not find any linear correlation among them. We next consider bandwidth requirements to retrieve movie trailer contents. Our objective is to make it possible for user to view the contents in real-time. Many previous studies investigate bandwidth requirement based only on the file size distribution. In this paper, we analyze the traffic design criteria for CDN or P2P by taking into account both of the results for the file size distribution and the relationship between playing duration and file size for movie trailers. Simulation studies reveal the impact for the bandwidth requirement.

When people watch such motion pictures as documentaries or educational-type films, it is very natural for them to be interested in moving objects in the movies and be eager to know the detailed information related to these object. Therefore, a mechanism that enables users to directly pick up object information from motion pictures is necessary to make a movie system feasible. For this reason, we are researching techniques on using objects in motion pictures as hypermedia anchors. We call a movie system that provides the above mechanism a video hypermedia system. An object in a motion picture can generally be considered as a complex object which includes many parts. To allow users to obtain information related to each part, a system must be able to provide anchors corresponding to each part in each complex object. For this, authors cannot help defining all anchors in all frames, since the visual status of each part varies from moment to moment. This paper presents our approach for managing objects in motion pictures for video hypermedia systems. The main feature of the proposed method is to apply computer graphic techniques to the defining of anchors for a complex object.

A real-time read/write motion picture has been demonstrated by hole-burning holography using cryogenic Eu3+: Y2SiO5 crystal. In a holographic configuration the laser frequency was continuously scanned within the 7F0-5D0 absorption line while the object was in motion. This movie has no picture frames, and therefore is temporally continuous. This feature allows realization of high-speed and high-time-resolution motion recording.