Faculty Profiles - Noboru Babaguchi

Papers - Noboru Babaguchi

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Example-based video remixing support system Reviewed

Naoko Nitta, Noboru Babaguchi

MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops 563 - 572 2011

Video remixes are generally created by sequentially arranging selected video clips and mixing them with other media streams such as audio clips and transition effects. Especially, mixing music clips often effectively improves the expressive quality of video clips. This paper proposes an example-based system for supporting average users in the 3 steps in video remixing: I)video shot sequence creation, II)music clip selection, and III)audio volume adjustment. The proposed system creates a template for a video remix and gives suggestions to users on an interface such as which video clips should be selected to create a video shot sequence and which music clips should be mixed to the created video shot sequence based on professionally created video remix examples. Then, the audio volume of each video shot is automatically adjusted based on its audio content so that the sounds in the video shots and the music clips would not interfere with each other. Experiments have verified that our system was able to create a video shot sequence whose quality was improved equally as the professionally created one by mixing the selected music clips, doubling the subjective scores from 1.7 to 3.7 on a scale of 1-5. Automatic audio volume adjustment improved the subjective scores by approximately 0.5 points on average. Further, the suggestions provided on the interface was evaluated useful by 5 subjects when creating a video remix by selecting 32 video clips and 4 music clips from 265 video clips and 180 music clips. © 2011 ACM.

Example-based video remixing for home videos

Naoko Nitta, Noboru Babaguchi

Proceedings - IEEE International Conference on Multimedia and Expo 2011

Video remixes are generally created by sequentially arranging selected video clips and combining them with other media streams such as audio clips. In this paper, an example-based approach is adopted for semi-automatically creating video remixes of good expressive quality from home videos. Given multiple home video clips and audio clips, the proposed system generates a video remix by four processes: I)video clip sequence generation, II)audio clip selection, III)audio boundary extraction, and IV)video segment extraction based on professionally created video remix examples. A user interface which presents video clips according to their suitability to the examples and their perceived quality is developed so that users can efficiently and effectively select and arrange suitable video clips in video clip sequence generation. By using movie trailers of action genre as video remix examples, a 43-second video remix was created from 45-minute home videos and was subjectively evaluated better than the one created considering only the perceived quality of video clips. © 2011 IEEE.

Content-preserving zoom-in view generation for surveillance videos Reviewed

Kenji Watanabe, Naoko Nitta, Noboru Babaguchi

COMPUTATIONAL IMAGING IX 7873 2011

There are several zoom-in video display methods including full-zoom and fisheye view that magnify the regions of interest (ROIs). However, those methods usually discard or deform the remaining regions without considering their content. In this paper, we propose a method for generating a content-preserving zoom-in view which magnifies ROIs and at the same time preserves the content of the remaining regions. Targeting on surveillance videos, our method firstly extracts moving objects from every input frame as ROIs. Then, the importance score is calculated for each pixel in the input frame based on its content to determine where the deformation, which may cause the destruction of the content, should be avoided. Finally, a mapping problem from the input frame to the zoom-in view with respect to the importance score is formulated to deform less important regions more than the important ones. Experiments are conducted to study the effectiveness of considering the content importance. We also compare the results of our method with those of other methods, fisheye view and a method of using uniform scaling and seam carving.

Image Retrieval Considering People Co-occurrence Relations Using Relevance Feedback Reviewed

Kazuya Shimizu, Naoko Nitta, Noboru Babaguchi

MULTIMEDIA ON MOBILE DEVICES 2011 AND MULTIMEDIA CONTENT ACCESS: ALGORITHMS AND SYSTEMS V 7881 2011

The recent popularity of digital cameras allows us to take a large number of images. There is an increasing need for efficiently and accurately retrieving images containing a specific person from such image collections. While only the visual features of the specific person are used in many query-by-example retrieval methods, we focus on the fact that some people such as family or friends are more likely to appear in the same images than others and use visual features of not only the queried person but also people who have strong co-occurrence relations with the queried person to improve the retrieval performance. The relevance feedback is used to learn who co-occur with the queried person in the same images, their faces, and the strength of their co-occurrence relations. For 116 images collected from 6 persons, after five feedback iterations, the recall rate of 53% was obtained by considering the co-occurrence relations among people, as against 34% when using only features of the queried person.

Learning people co-occurrence relations by using relevance feedback for retrieving group photos

Kazuya Shimizu, Naoko Nitta, Noboru Babaguchi

Proceedings of the 1st ACM International Conference on Multimedia Retrieval, ICMR'11 2011

This paper proposes an image retrieval method which retrieves images of a specific person from group photos. Many query-by-example methods have focused only on the visual features of the queried person. However, since socially related people such as family and friends are often taken photos together, their co-occurrence relations can be useful information. Thus, we propose an image retrieval method which uses the visual features of not only the queried person but also those who co-occur with the queried person in the same images. Relevance feedback is used to learn who co-occur with the queried person, their faces, and how strong their co-occurrence relations are. When retrieving the images of 19 persons in total from 158 images, after five feedback iterations, the recall rate of 50% was obtained by considering the people co-occurrence relations, as against 33% when considering only the queried person. With human errors in giving relevance feedback, the recall rate still improved to 40%. © 2011 ACM.

Three-level privacy control for sensing-based real-world content digital diorama

Takumi Takehara, Naoko Nitta, Noboru Babaguchi

ACM International Conference Proceeding Series 17 - 20 2011

Digital Diorama, the sensing-based real-world content, can be constructed by integrating real-time information obtained from sensors monitoring the real world. In order to increase the benefits of viewers without violating the privacy of monitored persons, this paper proposes three-level privacy control over the monitored persons based on their agreement to the usage of their information obtained from sensors: privacy control with i) no agreement, ii) partial agreement. and iii) mutual agreement. i) presents only their positions to show where persons are. ii) additionally presents the information which can be automatically obtained from sensors such as age and gender to show what kinds of persons are where without disclosing the visual appearances. iii) presents their visual appearances based on their mutual agreement with specific viewers. Our evaluation indicated that the representation simulating each privacy control presented information from sensors with acceptable privacy protection. © 2011 ACM.

Fast extraction method of high-level feature using random forests from imbalanced training data Reviewed

Y. Kawai, H. Sumiyoshi, M. Fujii, M. Shibata, N. Babaguchi

Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers 64 ( 12 ) 1951 - 1955 2010.12

We propose a method of using a random forest algorithm to quickly detect semantically high-level features such as specific objects. The random forest has a lower computation cost than that of the common algorithm such as a support vector machine (SVM). However, it cannot cope with training data that have a large bias in the number of negative and positive examples. We improve the conventional training algorithm to ensure sampling the data with equal probability from each class when creating bootstrap samples, which increases the classification accuracy. Experiments on the Caltech-101 dataset resulted in a recall of 64.3% and precision of 71.1%, which were comparable to those of conventional methods. The average time needed for training and for detection were reduced to one sixteenth and one twenty-seventh that of SVM, respectively.

[Invited Speech] Visual Processing for Privacy-Sensitive Information Invited

Noboru Babaguchi

2010.10

A new spatio-temporal method for event detection and personalized retrieval of sports video Reviewed

Minh-Son Dao, Noboru Babaguchi

MULTIMEDIA TOOLS AND APPLICATIONS 50 ( 1 ) 227 - 248 2010.10

In this paper, a new spatio-temporal method for adaptively detecting events based on Allen temporal algebra and external information support is presented. The temporal information is captured by presenting events as the temporal sequences using a lexicon of non-ambiguous temporal patterns. These sequences are then exploited to mine undiscovered sequences with external text information supports by using class associate rules mining technique. By modeling each pattern with linguistic part and perceptual part those work independently and connect together via transformer, it is easy to deploy this method to any new domain (e.g baseball, basketball, tennis, etc.) with a few changes in perceptual part and transformer. Thus the proposed method not only can work well in unwell structured environments but also can be able to adapt itself to new domains without the need (or with a few modification) for external re-programming, re-configuring and re-adjusting. Results of automatic event detection progress are tailored to personalized retrieval via click-and-see style using either conceptual or conceptual-visual query scheme. Experimental results carried on more than 30 hours of soccer video corpus captured at different broadcasters and conditions as well as compared with well-known related methods, demonstrated the efficiency, effectiveness, and robustness of the proposed method in both offline and online processes.

Constructing Distributed Hippocratic Video Databases for Privacy-Preserving Online Patient Training and Counseling Reviewed

Jinye Peng, Noboru Babaguchi, Hangzai Luo, Yuli Gao, Jianping Fan

IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE 14 ( 4 ) 1014 - 1026 2010.7

Digital video now plays an important role in supporting more profitable online patient training and counseling, and integration of patient training videos from multiple competitive organizations in the health care network will result in better offerings for patients. However, privacy concerns often prevent multiple competitive organizations from sharing and integrating their patient training videos. In addition, patients with infectious or chronic diseases may not want the online patient training organizations to identify who they are or even which video clips they are interested in. Thus, there is an urgent need to develop more effective techniques to protect both video content privacy and access privacy. In this paper, we have developed a new approach to construct a distributed Hippocratic video database system for supporting more profitable online patient training and counseling. First, a new database modeling approach is developed to support concept-oriented video database organization and assign a degree of privacy of the video content for each database level automatically. Second, a new algorithm is developed to protect the video content privacy at the level of individual video clip by filtering out the privacy-sensitive human objects automatically. In order to integrate the patient training videos from multiple competitive organizations for constructing a centralized video database indexing structure, a privacy-preserving video sharing scheme is developed to support privacy-preserving distributed classifier training and prevent the statistical inferences from the videos that are shared for cross-validation of video classifiers. Our experiments on large-scale video databases have also provided very convincing results.

Theoretical Analysis of the Performance of Anonymous Communication System 3-Mode Net Reviewed

Kazuhiro Kono, Shinnosuke Nakano, Yoshimichi Ito, Noboru Babaguchi

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES E93A ( 7 ) 1338 - 1345 2010.7

This paper aims at analyzing the performance of an anonymous communication system 3-Mode Net with respect to the number of relay nodes required for communication and sender anonymity. As for the number of relay nodes, we give explicit formulas of the probability distribution, the expectation, and the variance. Considering sender anonymity, we quantify the degree of sender anonymity under a situation where some relay nodes collude with each other. The above analyses use random walk theory, a probability generating function, and their properties. From obtained formulas, we show several conditions for avoiding a situation where the number of relay nodes becomes large, and for providing high sender anonymity. Furthermore, we investigate the relationship between the number of relay nodes and sender anonymity, and give a condition for providing a better performance of 3MN.

Recoverable Privacy Protection for Video Content Distribution Reviewed

Guangzhen Li, Yoshimichi Ito, Xiaoyi Yu, Naoko Nitta, Noboru Babaguchi

EURASIP Journal on Information Security 2009 Article No. 293031 - 11 pages 2010.1

This paper presents a method which attains recoverable privacy protection for video content distribution. The method is based on discrete wavelet transform (DWT), which generates scaling coefficients and wavelet coefficients. In our method, scaling coefficients, which can be regarded as a low-resolution image of an original image, are used for producing privacy-protected image. On the other hand, wavelet coefficients, which can be regarded as privacy information, are embedded into the privacy-protected image via information hiding technique. Therefore, privacy protected image can be recovered by authorized viewers if necessary. The proposed method is fully analyzed through experiments from the viewpoints of the amount of the embedded privacy information, the deterioration due to the embedding, and the computational time. © 2009 Guangzhen Li et al.

Automated generation method for TV program trailers based on introductory text Reviewed

Yoshihiko Kawai, Hideki Sumiyoshit, Masahiro Shibata, Nobuyuki Yagi, Noboru Babaguchi

Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers 64 ( 1 ) 85 - 93 2010.1

Video summarization is one of the most efficient methods for retrieval from large video archives. An automated method is described for generating TV program trailers (short video clips to advertise the program). Our method uses introductory text from an electronic program guide, which is a short description of the program highlights. We assume that the video segments corresponding to closed caption sentences with similar expressions to those of the introductory text contain appealing scenes, and our system generates a program trailer by linking these segments together. The AdaBoost algorithm is used to learn the textual characteristics of the introductory text. The proposed method was used to summarize actual TV programs to test its effectiveness.

Automatically protecting privacy in consumer generated videos using intended human object detector Reviewed

Yuta Nakashima, Noboru Babaguchi, Jianping Fan

MM'10 - Proceedings of the ACM Multimedia 2010 International Conference 1135 - 1138 2010

The growing popularity of video sharing services such as YouTube enables us to upload and share consumer generated videos (CGVs) easily, resulting in disclosure of the privacy sensitive information (PSI) of persons, i.e., their appearances. Therefore, we need a technique for automatically protecting the privacy in CGVs
however, the main problem is how to determine PSI regions automatically. In this paper, we propose a novel system for automatically protecting the privacy in CGVs. The proposed system tackles the problem of determining PSI regions by using an intended human object detector that detects human objects which the camera person wanted to capture to achieve his/her capture intention. In addition, the proposed system adopts several PSI obscuring methods such as blocking out, blurring and seam carving. We present the results of subjective evaluations of a privacy protected video in terms of the visual quality and acceptability of PSI disclosure, as well as the performance of the intended human object detector. © 2010 ACM.

Face Image Retrieval across Age Variation Using Relevance Feedback Reviewed

Naoko Nitta, Atsushi Usui, Noboru Babaguchi

ADVANCES IN MULTIMEDIA MODELING, PROCEEDINGS 5916 152 - 162 2010

Given a single face image of a specific person as a query, it is very difficult to retrieve all of his/her images from a personal image collection stored for a long term clue to age-related changes in facial appearances. This paper proposes to apply relevance feedback to enhance the performance of image retrieval from the image collections with age variation. Specifically, we propose two types of update schemes: i) query expansion and ii) weight updating and show the effects of each scheme by experiments with two actual image collections. For an image collection, the recall rate improved from 40.8% to 72.5% after five iterations of relevance feedback.

EVENT TACTIC ANALYSIS IN SPORTS VIDEO USING SPATIO-TEMPORAL PATTERN Reviewed

Minh-Son Dao, Keita Masui, Noboru Babaguchi

2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING 1497 - 1500 2010

Recently, event detection in sports videos has been gaining some remarkable results. Unfortunately, there is a lack of useful tools for users to explore and exploit these event clips on their own demands. In this paper, a novel method using spatio-temporal patterns to analyze event tactics in sports videos is introduced. The proposed method aims to understand tactics of events such as distributions and speeds of players, or attacking/defensive formations throughout a time when such events happen without tracking objects. The major contribution of the proposed method is to model event tactics by using sequence of symbols. Each symbol represents a distribution of players in a certain period of time. Therefore, a sequence of symbols intrinsically is concerned as spatio-temporal patterns. By using these patterns, an event tactic is detected, explained, and integrated into an event video to create a visualizing abstract. This visualizing abstract is very useful to help users understand an event tactic without watching whole clip. Moreover, users could query by an example or by a text to find all events sharing the same tactic. Thorough testing with over 100 goal clips in soccer domain demonstrate the superiority of the proposed method in terms of precision recall ratios.

Discriminating intended human objects in consumer videos Reviewed

Hiroshi Uegaki, Yuta Nakashima, Noboru Babaguchi

Proceedings - International Conference on Pattern Recognition 4380 - 4383 2010

In a consumer video, there are not only intended objects, which are intentionally captured by the camcorder user, but also unintended objects, which are accidentally framed-in. Since the intended objects are essential to present what the camcorder user wants to express in the video, discriminating the intended objects from the unintended objects are beneficial for many applications, e.g., video summarization, privacy protection, and so forth. In this paper, focusing on human objects, we propose a method for discriminating the intended human objects from the unintended human objects. We evaluated the proposed method using 10 videos captured by 3 camcorder users. The results demonstrate that the proposed method successfully discriminates the intended human objects with 0.45 of recall and 0.80 of precision. © 2010 IEEE.

Digital diorama: Sensing-based real-world visualization Reviewed

Takumi Takehara, Yuta Nakashima, Naoko Nitta, Noboru Babaguchi

Communications in Computer and Information Science 81 663 - 672 2010

Many sensors around the world are consistently collecting the real-time real-world data. The data streams captured by these sensors can give us an idea of what is going on in a specific area
however, it is not easy for humans to understand their spatial and temporal relationships by just looking at them independently. This paper proposes to construct Digital Diorama, a three-dimensional view where viewers can see at a glance how people are moving around the monitored space without violating their privacy, by integrating multiple data streams captured by stationary cameras and RFID readers in real time. Digital Diorama realizes such real-world visualization with the following features: 1) view control, 2) real-time camera image superimposition, and 3) privacy control. We have demonstrated that Digital Diorama for a shopping center was able to present the current positions of persons and real-time camera images in approximately 1 frame per second. © Springer-Verlag Berlin Heidelberg 2010.

Detecting intended human objects in human-captured videos Reviewed

Yuta Nakashima, Noboru Babaguchi, Jianping Fan

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010 33 - 40 2010

When people take videos, they always want to capture intended objects, which are essential for presenting what they want to express in their videos, and to share the intended objects with others. The concept of intended objects provide a novel perspective for video content analysis, and detecting intended objects may be beneficial for wide range of applications such as video understanding and semantics interpretation, video summarization, video adaptation, video privacy protection, and so on. In this paper, we focus on a particular type of intended objects, i.e., intended human objects, and an interesting method is developed for detecting intended human objects automatically from human-captured videos. We also investigate the correlation between intended human objects and visual attention. Our experimental results indicate that our method can successfully detect the intended human objects. © 2010 IEEE.

Hierarchical anomality detection based on situation Reviewed

Shuichi Nishio, Hiromi Okamoto, Noboru Babaguchi

Proceedings - International Conference on Pattern Recognition 1108 - 1111 2010

In this paper, we propose a novel anomality detection method based on external situational information and hierarchical analysis of behaviors. Past studies model normal behaviors to detect anomality as outliers. However, normal behaviors tend to differ by situations. Our method combines a set of simple classifiers with pedestrian trajectories as inputs. As mere path information is not sufficient for detecting anomality, trajectories are first decomposed into hierarchical features of different abstract levels and then applied to appropriate classifiers corresponding to the situation it belongs to. Effects of the methods are tested using real environment data. © 2010 IEEE.

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Papers - Noboru Babaguchi