Papers - Noboru Babaguchi

Discrimination between Handwritten and Computer-Generated Texts using a Distribution of Patch-Wise Font Features Reviewed

N. Hamasaki, K. Nakamura, N. Nitta, N. Babaguchi

Proc. of Asia-Pacific Signal and Processing Association Annual Summit and Conference (APSIPA ASC 2019)   2019.11

Generating Spoofing Tweets considering Points of Interest of Target User Reviewed

J. Lim, N. Nitta, K. Nakamura, N. Babaguchi

Proc. of Asia-Pacific Signal and Processing Association Annual Summit and Conference (APSIPA ASC 2019)   2019.11

Discrimination between Genuine and Cloned Gait Silhouette Videos via Autoencoder-based Training Data Generation Reviewed

Y. Hirose, K. Nakamura, N. Nitta, N. Babaguchi

IEICE Transactions on Information and Systems   E102.D ( 12 )   2535 - 2546   2019.9

Constructing Geographic Dictionary from Streaming Geotagged Tweets Reviewed

J. Lim, N. Nitta, K. Nakamura, N. Babaguchi

ISPRS International Journal on Geo-Information   8 ( 5 )   Article No. 216 - 24 pages   2019.5

Encryption-Free Framework of Privacy-Preserving Image Recognition for Photo-Based Information Services Reviewed

K. Nakamura, N. Nitta, N. Babaguchi

IEEE Transactions on Information Forensics and Security   14 ( 5 )   1264 - 1279   2019.5

A logical consideration on deceived person's thinking Reviewed

S. Myojin, N. Babaguchi

ARTIFICIAL LIFE AND ROBOTICS   24 ( 1 )   114 - 118   2019.3

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The problem that old people are sometimes deceived by means of remittance fraud has become a great concern in our society. In this paper, we consider deceived person's thinking using Barwise-Seligman's framework, which is a logic for representing distributed systems among people or artifacts. The framework has been used to consider the conversation with comical misconception. We think that it is similar to remittance fraud because in telephone conversation, a criminal of the fraud uses victim's misconception so that the criminal can impersonate somebody. In this paper, we consider a logical system to describe the communication of a typical remittance fraud, and discuss the representative ability of the formulas to express the situation where a person is deceived or not deceived. The formulas have indicated that a person may be deceived as a result of handling exceptions in terms of logic. This paper contributes to providing a novel viewpoint to consider why people are deceived.

Semiotic and Logical Approach for Analysis of Augmented World Reviewed

S. Myojin, N. Babaguchi

Proc. of 12th Asia Pacific Workshop on Mixed and Augmented Reality (APMAR2019)   2019.3

Modeling deceptive communication based on information flow Reviewed

S. Myojin, N. Babaguchi

Proc. of International Symposium on Artificial Life and Robotics, AROB 24th 2019   2019.1

A Comic-Style Chat System with Japanese Expression Techniques for More Expressive Communication. Reviewed

J. Itou, K. Matsumura, J. Munemori, N. Babaguchi

Collaboration Technologies and Social Computing - 25th International Conference(CRIWG/CollabTech)   172 - 187   2019

TRAINING-FREE METHOD FOR GENERATING MOTION VIDEO CLONES FROM A STILL IMAGE CONSIDERING SELF-OCCLUSION OF HUMAN BODY Reviewed

T. Tsutsumi, K. Nakamura, S. Myojin, N. Nitta, N. Babaguchi

2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)   509 - 513   2019

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In this paper, we propose a method for generating photorealistic video in which a person virtually performs a motion that is not performed in the real world. we refer to such video as motion video clones (MVCs). The proposed method requires only two kinds of source information as input data: a reference video, in which a person A performs some motion, and a target image, which includes the whole body of another person B. Using these data, our method generates a MVC in which the person A's motion is re-enacted by the person B's body. Since our method does not need 3D human body model nor any training phase, it is suitable to MVC-based entertainment systems. To handle the self-occlusion of the human body in the reference video, we employ a part-based approach. For each part such as the right arm and the left leg, we first extract its skeleton from the target image and move it so that the motion represented by the reference video is re-enacted. Next, we compute a 2D affine transform between the original and moved positions of the skeleton. This transform is used to map the texture of the target image onto each frame of a resultant MVC. Finally, we extend the part-wise affine transforms to pixel-wise ones by computing their linear combination for each pixel, whose combination weights are computed according to the geodesic distance between the pixel and the center of each part. This allows us to avoid unnatural appearance around the joints of the body parts. In our experiments, the proposed method generated much visually-natural MVCs than existing methods.

Passive Video Forgery Detection Considering Spatio-Temporal Consistency Reviewed

K. Kono, T. Yoshida, S. Ohshiro, N. Babaguchi

Proceedings of 14th International Conference on Information Assurance and Security   2018.12

Initial Consideration on Human Factor in Security Incident Reviewed

S. Myojin, N. Babaguchi

Proc. of The 13th International Workshop on Security   2018.9

Generating Handwritten Character Clones from an Incomplete Seed Character Set using Collaborative Filtering Reviewed

K. Nakamura, E. Miyazaki, N. Nitta, N. Babaguchi

68 - 73   2018.8

Extracting Related Real-World Observations from Microblog Reviewed

N. Nitta, M. Yoshitake, K. Nakamura, N. Babaguchi

vol.16-J   Article No. 22 - 8 pages   2018.3

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8 pages

Formulating what a deceived person thinks Reviewed

S. Myojin, N. Babaguchi

23rd International Symposium on Artificial Life and Robotics, AROB 23rd 2018   2018.1

Development of a Stroll Support System Using Route Display on a Map and Photograph Sharing Service. Reviewed

J. Itou, T. Mori, J. Munemori, N. Babaguchi

Proc. of 10th International Conference on Collaboration Technologies (CollabTech2018)   48 - 55   2018

Constructing Geospatio-Temporal Concept Graphs from Tagged Images Reviewed

H. Honjo, N. Nitta, K. Nakamura, N. Babaguchi

Proceedings - 2017 IEEE 3rd International Conference on Multimedia Big Data, BigMM 2017   169 - 176   2017.6

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This paper proposes a method for discovering the knowledge about geospatio-temporal concepts, which are strongly related to specific locations and times, from images tagged with latitude and longitude coordinates, time-stamps, and textual tags. The proposed method firstly extracts textural tags used either in specific locations or times as the geospatial or temporal concepts with their location or time information. Then, the semantic relations among the geospatio-temporal concepts are extracted based on the co-occurrence of the corresponding tags to be represented as a graph. Finally, visually discriminative geospatio-temporal concepts are linked to representative visual concepts. The usefulness of the discovered knowledge is evaluated based on the automatic tagging for the images tagged with latitude and longitude coordinates and time-stamps.

Extracting Real-World Observations from Microblog Reviewed

M. Yoshitake, Naoko Nitta, Kazuaki Nakamura, Noboru Babaguchi

Proceedings - 2017 IEEE 3rd International Conference on Multimedia Big Data, BigMM 2017   232 - 237   2017.6

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Since a large number of users of various social networking services post what they observe around themselves, what is going on around the world can be known in real time by extracting such real-world observations. Especially, observations covering miscellaneous areas of interest are posted to Twitter as short text messages. Our goal is to extract such observations to better understand the current situations of the real world. Since the observations at specific locations are often described with words representing the observed locations or events, the locations or events all over the world can be discovered by finding such local words which are uniquely used at specific locations or times. Then, parts of their observations can be obtained by using the local words to define the semantics of each local word. Finally, the observations which do not contain the local words but are related to the locations or events can be extracted based on their semantic relevancy to each local word.

On-line Geospatial Term Extraction from Streaming Geotagged Tweets Reviewed

T. Kamimura, N. Nitta, K. Nakamura, N. Babaguchi

Proceedings - 2017 IEEE 3rd International Conference on Multimedia Big Data, BigMM 2017   322 - 329   2017.6

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Recently, geotagged posts to social media such as Twitter have become major sources for geospatial information referenced to a set of geographic coordinates. Especially, many existing work collects geospatial terms which identify geographic locations by examining the spatial locality of the term usage patterns observed in the geotagged posts accumulated for a certain period of time. Although the spatial locality of the collected geospatial terms can only be temporary, such time variability difference among the geospatial terms have not been considered in the existing work. Thus, in order to separately collect the stationary and temporary geospatial terms with proper timing, we propose an on-line method for constructing a geographical dictionary containing the up-to-date geospatial terms and their locations by continuously examining the spatial locality of terms in streaming geotagged posts. The geospatial terms can be distinguished between stationary and temporary terms according to their usage patterns in the recent set of geotagged posts and their locations recorded in the geographical dictionary. Additionally, images representing each geospatial term can also be collected from the posts containing the corresponding term. The usefulness of the collected geospatial information is demonstrated in comparison to existing geographical dictionaries constructed by experts, crowdsourcing, and batch method.

Detection of groups in crowd considering their activity state Reviewed

K. Nakamura, T. Ono, N. Babaguchi

Proceedings - International Conference on Pattern Recognition   277 - 282   2017.4

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In this paper, we focus on the problem of group detection in crowd, which is a task of partitioning a set of pedestrians in a scene into small subsets called groups based on their trajectories. Most of previous methods use only a single model for representing a relationship between trajectories of pedestrians who belong to the same group. However, such relationship would vary depending on the activity state (e.g. walking together, approaching, splitting, and so on) of the group. In this paper, we propose a novel group detection method which can cope with a variation of groups' activity state. The proposed method constructs different models for each activity state in order to appropriately evaluate the relationship of pedestrians' trajectories. In addition, our method regards groups' activity state as hidden variables and estimates their probability distributions, which is used for integrating the constructed models. The proposed method outperforms existing methods in the experiment on the public dataset.