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Abstract: We propose a camera-based method for digital recovery of handwritings on ordinary paper. Our method is characterized by the following two points: (1) it requires no special device such as special paper other than a camera-pen to recover handwritings, (2) if the handwriting is on a printed document, the method is capable of localizing it onto an electronic equivalent of the printed document. The above points are enabled by the following processing. The handwriting is recovered by the LK tracking to trace the move of the pen-tip. The recovered shape is localized onto the corresponding part of the electronic document with the help of document image retrieval called LLAH (locally likely arrangement hashing). A new framework for stably estimating the homography from a camera-captured image to the corresponding electronic document allows us to localize the recovered handwritings accurately. We experimentally evaluate the accuracy, processing time and memory usage of the proposed method using 30 handwritings. From the comparison to other methods that implement alternative ways for realizing the same functionality, we have confirmed that the proposed method is superior to those other methods. [Copyright &y& Elsevier]

Manga, a kind of Japanese comic book, is an important genre in the realm of image publications requiring copyright protection. To copy manga, illegal users generally focus on certain interesting parts from which to make partial copies to apply in their own drawings. With respect to their sources, copying of manga can be divided into two types: (1) exact copies, which duplicate specific contents of manga, such as scanned manga publications (printed copies) and traced outlines of manga (hand-drawn copies), and (2) similar partial copies, which infringe the copyright of manga characters based on their features. In this paper, we propose applying content-based image retrieval methods to detect both exact and similar copies based on two kinds of regions of interest (ROIs): generic ROIs and face ROIs. The method is able not only to locate the partial copies from images with complex backgrounds, but also to report the corresponding copied parts of copyrighted manga pages for exact copy detection and copied manga characters for similar copy detection. The experimental results prove high performance of the proposed method for detecting printed partial copies. In addition, 85 % of hand-drawn and 77 % of similar partial copies were detected with relatively high precision using a database containing more than $$10{,}000$$ manga pages. [ABSTRACT FROM AUTHOR]

In this paper, we propose a system for recommending tags for images. The proposed method presents to the user various tags with high precision by taking into account both the co-occurrence of tags and tags for similar images. Additional searches with user feedback enable us to find some new tags relevant to the image of interest. In order to test the proposed method, we compared it with a method based only on the co-occurrence of tags, as well as a method based only on the similarity of images. From the experimental results using 16,002 images, we have confirmed that the proposed method is capable of finding more tags compared to the methods used for comparison. We have also confirmed that the additional search is effective for finding additional tags. © 2011 Wiley Periodicals, Inc. Electron Comm Jpn, 94(12): 57-64, 2011; Published online in Wiley Online Library (). DOI 10.1002/ecj.10342 [ABSTRACT FROM AUTHOR]

Attentional orienting towards others' gaze direction or pointing has been well investigated in laboratory conditions. However, less is known about the operation of attentional mechanisms in online naturalistic social interaction scenarios. It is equally plausible that following social directional cues (gaze, pointing) occurs reflexively, and/or that it is influenced by top-down cognitive factors. In a mobile eye-tracking experiment, we show that under natural interaction conditions, overt attentional orienting is not necessarily reflexively triggered by pointing gestures or a combination of gaze shifts and pointing gestures. We found that participants conversing with an experimenter, who, during the interaction, would play out pointing gestures as well as directional gaze movements, continued to mostly focus their gaze on the face of the experimenter, demonstrating the significance of attending to the face of the interaction partner—in line with effective top-down control over reflexive orienting of attention in the direction of social cues. [ABSTRACT FROM AUTHOR]

The integration of ubiquitous technologies in the field of education has considerably enhanced our way of learning. Such technologies enable students to get a gradual feedback about their performance and to provide adapted learning materials. It is particularly important in the domain of foreign language learning which requires intense daily practice. One of the main inputs of adaptive learning systems is the user’s understanding of a reading material. The reader’s understanding can be divided into two parts: the objective understanding and the subjective understanding. The objective understanding can be measured by comprehension questions about the content of the text. The subjective understanding is the reader’s perception of his own understanding. The subjective understanding plays an important role in the reader’s motivation, self-esteem and confidence. However, its automatic estimation remains a challenging task. This paper is one of the first to propose a method to estimate the subjective understanding. We show that using the eye gaze to predict the subjective understanding improves the estimation by 13% as compared to using comprehension questions. [ABSTRACT FROM AUTHOR]

Wearable devices offer a wealth of data for ubiquitous computing researchers. For instance, sleep data from a wearable could be used to identify an individual's harmful habits. Recently, devices which are unobtrusive in size, setup, and maintenance are becoming commercially available. However, most data validation for these devices come from brief, short-term laboratory studies or experiments which have unrepresentative samples that are also inaccessible to most researchers. For wearables research conducted in-the-wild, the prospect of running a study has the risk of financial costs and failure. Thus, when researchers conduct in-the-wild studies, the majority of participants tend to be university students. In this paper, we present a month-long in-the-wild study with 31 Japanese adults who wore a sleep tracking device called the Oura ring. The high device usage results found in this study can be used to inform the design and deployment of longer-term mid-size in-the-wild studies. [ABSTRACT FROM AUTHOR]

SUMMARY Specific object recognition methods based on the exact matching of feature vectors are known as methods that can achieve high recognition performance for large-scale three-dimensional specific object recognition. Since there are few common three-dimensional object datasets whose size is sufficient to explore the effect of differences in object dataset composition and the effect of increasing number of objects for recognition, these effects for specific object recognition methods based on exact matching of feature vectors have been discussed insufficiently. The number of objects in well-known datasets (e.g., COIL-100) is around 100. Therefore, in this research, we prepared a dataset of 1002 three-dimensional objects by themselves. In this paper, we discuss the effect of dataset differences, which are based on object structure, texture, and the number of objects, for methods such as that based on the Bloomier filter and that based on a hash table with this dataset in addition to COIL-100. © 2013 Wiley Periodicals, Inc. Electron Comm Jpn, 96(9): 33-45, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11414 [ABSTRACT FROM AUTHOR]

Applying mobile sensing technology to cognitive tasks will enable novel forms of activity recognition. [ABSTRACT FROM PUBLISHER]

In order to make collaborative business activities fruitful, it is essential to know characteristics of organizations and persons in more details and to gather information relevant to the activities. In this paper, we describe a notion of “information recycling” that actualizes these requirements by analyzing documents. The key of recycling information is to utilize annotations on documents as clues for generating user profiles and for weighting contents in the context of the activities. We also propose a method of extracting annotations on paper documents just by pressing one button with the help of techniques of camera-based document image analysis. Experimental results demonstrate that it is fundamentally capable of acquiring annotations on paper documents on the condition that their electronic versions without annotations are available for the processing. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 165(2): 60–68, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20516 [ABSTRACT FROM AUTHOR]

The automated generation of fonts containing a large number of characters is in high demand. For example, a typical Japanese font requires over 1000 characters. Unfortunately, professional typographers create the majority of fonts, resulting in significant financial and time investments for font generation. The main contribution of this article is the development of a method that automatically generates a target typographic font containing thousands of characters, from a small subset of character images in the target font. We generate characters other than the subset so that a complete font is obtained. We propose a novel font generation method with the capability to deal with various fonts, including a font composed of distinctive strokes, which are difficult for existing methods to handle. We demonstrated the proposed method by generating 2965 characters in 47 fonts. Moreover, objective and subjective evaluations verified that the generated characters are similar to the original characters. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present a novel digital pen device, called data-embedding pen, for enhancing the value of handwriting on physical paper. This pen produces an additional ink-dot sequence along a written stroke during writing. This ink-dot sequence represents arbitrary information, such as writer’s name and writing date. Since the information is placed on the paper as an ink-dot sequence, it can be retrieved just by scanning or photographing the paper. In addition to the hardware of the data-embedding pen, this paper also proposes a coding scheme for reliable data-embedding and retrieval. In fact, the physical data-embedding on a paper will undergo various severe errors and therefore a robust coding scheme is necessary. Through experiments on data written by two writers, we show that we can embed 32 bits on short and simple or even on more complex patterns and finally retrieve them with a high reliability. [Copyright &y& Elsevier]

Recognizing characters in scene images suffering from perspective distortion is a challenge. Although there are some methods to overcome this difficulty, they are time-consuming. In this paper, we propose a set of affine-invariant features and a new recognition scheme called 'progressive removing' that can help reduce the processing time. Progressive removing gradually removes less feasible categories and skew angles by using multiple classifiers. We observed that progressive removing and the use of the affine invariant features reduced the processing time by about 60% in comparison to a trivial algorithm without decreasing the recognition rate. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 180(2): 55-63, 2012; Published online in Wiley Online Library (). DOI 10.1002/eej.22276 [ABSTRACT FROM AUTHOR]