Sampling patterns with a blue noise distribution are widely used in many areas of computer graphics, yet their efficient generation remains a difficult problem. We propose a method to generate point sets with a blue noise distribution using a deterministic algorithm with no preprocessing. We insert each new sample at the center of the largest empty circle in the point set, which is obtained by calculating the Delaunay-triangulation of the set and finding the triangle with the largest circumcircle. Our method supports adaptive sampling according to a user-specified density function, as well as specifying the exact number of required samples. It can also be extended to perform sampling on a three-dimensional curved surface.

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This paper describes a new approach for passive measurements of transparent glass plate surfaces, in which the position distributions of the surfaces are obtained from virtual images of pattern boards taken with a camera. In the approach, structured patterns displayed on two boards are acquired with a camera through the surface and reflection points on the front and rear surfaces are located geometrically using the triangulation principle without any prior knowledge of the coordinates of other reflection points. This feature enables us to obtain a high spatial resolution of detection with high accuracy. In real-image experiments, reflection point position distributions on the planar glass plates of 3- to 10-mm in thickness were detected. The overall averages of position errors from the true are below 0.2 and 0.5mm along the lateral and vertical directions, respectively. The average of the error absolutes is less than 1mm and the standard deviation is less than 1.12mm for the lateral and vertical directions. Furthermore, it is made clear that the detection errors are caused by the quantization errors. The detection principle and system are simple, and the detection accuracy and spatial resolution, as well as the reliability, seem to be satisfactory enough for use in the inspection and production fields.

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This paper describes a new approach for accurately detecting scaling-change center positions of slightly scaling-changed images and also proposes a new technique for correcting the scaling changes. These approaches utilize the phase difference spectrum analysis approach for detecting image shifts and the technique for detecting scaling factors, without iterative approximation calculation. In experiments, three types of image patterns were used. When the position is within a few ten pixels from the image center, the detection accuracy of the scaling-change center position is 2.2 pixels on average and as high as 1.1 pixels, excluding errors for scaling-factor changes below ±0.6%. The correction accuracy for scaling factors is almost completely independent of the scaling-center position and is about 0.0004 on average. The pixel displacement of the corrected image from the reference image is about 0.012 pixels on average when the scaling-change center position is within a few ten pixels from the image center. From these results, it is clear that the proposed approaches, despite their simplicity, make it possible to detect scaling-change center positions for scaling-changed images and to correct the images with high accuracy and reliability.

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We propose an MPEG-2 to H.264 intra transcoding for interlace stream of frame and field macroblock intermingled to improve our previous work. This method uses an adaptive MB pair type selection method that keeps as many discrete cosine transform (DCT) coefficients of the original MPEG-2 bitstream as possible to avoid mixture of re-quantization noise. Experimental results show that the proposed method improves the peak signal-to-noise ratio (PSNR) values by about 0.33-1.55dB over those of the conventional methods.

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This paper proposes a restoration method for JPEG and blurred images based on ensemble learning algorithm. Such as a median filter, various restoration filters for these images have been already proposed and applied in real images. However, when images have edge and non-edge regions, it is difficult for single filter having fixed coefficients to reduce both blocky and mosquito noises adequately. Here, new restoration methods for JPEG and blurred images are proposed by introducing multiple muliti-layered neural networks. Each neural network can be adapted for edge, flat, and texture regions in images by ensemble learning. From experimental results, the proposed method can obtain good restoration accuracy compared with conventional filters. Moreover, we have confirmed that the proposed method could automatically assign restoration tasks to each neural network according to the characteristics of each region in given distorted images.

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In this paper, we propose an image classification method using local features and linear manifolds. In our method, local features such as SIFT are extracted from test and training images. In each class, all local features of training images are compressed by principal component analysis, thus a set of local features extracted from training images is represented by a linear manifold (affine subspace). In a voting phase, dissimilarity between a local feature extracted from a test image and each linear manifold is measured, and one vote is added to the class to which the nearest linear manifold belongs. Through voting by all test local features, the test image is then classified into the class that has majority votes. In this paper, we also adopt a steepest descent based learning algorithm to our classification rule for improving accuracy. The experimental results on the WANG image dataset verifies that our method performs as well or better than a nearest neighbor voting method using all training local features.

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This paper describes a detection method of pulmonary nodules (i.e. possible cancers) from chest X-ray computed tomography (CT) scans. The method consists of two phases. First, initial nodule candidates are detected by use of circle- and ring-shaped discriminant filters. Next, false positives such as blood vessels are reduced by use of radially-arranged rectangular discriminant filters and a view-based support vector machine. The proposed method is applied to actual CT scans, and experimental results are shown.

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In this paper, linear subspaces are used for detecting and retrieving rare cells called nucleated red blood cells (NRBCs) from microscope images. In our method, NRBCs are detected based on similarities between a candidate region and two subspaces spanned by NRBC images and their similar ones. After that, detected NRBC candidates are displayed to users in ascending order of the dissimilarities defined by the difference of similarities to each subspace. Furthermore, we derive a learning rule for our method for improving detection performance. Experimental results show that our method can detect NRBCs in about one second per microscope image and our learning can reduce the number of false detection.

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The digital road map is an important basis for the Intelligent Transport System and Geographic Information System; however, almost all digital maps are currently generated manually from paper maps. As it is very time consuming to generate digital road maps this way, we propose a system to generate digital maps using image processing of aerial images. Conventionally, most methods of road extraction use RGB features. However, the use in urban areas of RGB features has many problems as they are affected severely by shadows cast by buildings. On the other hand, road extraction using a Digital Surface Model (DSM) is not affected by shadows because a DSM is elevation data. However, it is too difficult to distinguish between a road and other objects, such as a railway, because the elevations of these objects are similar. In this paper, we use DSM and RGB aerial images to resolve the problems of each type of data. We segment a DSM to extract the road areas from the DSM; however, the segmentation method conventionally used could not extract narrow roads because that method is sensitive to noise in a DSM. In light of this, we next propose a method of image segmentation using Boundary code. The proposed segmentation method is robust against the noise in a DSM. In an experiment using actual data, the accuracy of road extraction using the proposed method was 83.7%, against the 76.0% achieved using the conventional method. In addition, the proposed method achieves faster segmentation than the conventional method. Moreover, this method extracted road areas more accurately in urban areas than by just using RGB or DSM.

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We have investigated a computer simulation method of color perception by elderly people. However, the previous method has two problems to be considered. That is, the luminescence spectrum of the display used in the experiments is not sufficiently examined, and there are some mismatches between the results of the artificial test through this simulator and the ones by the clinical test for elderly people using SPP color perception test. To improve this simulation method totally, in this work, (i) we utilize the actual luminescence emission spectrum measured for the LCD display used in the experiments. Also, (ii) we relax the color constancy hypothesis so that the lenticular yellowing changes not only luminosity but also chromaticity in color perception. Experimental results suggest that the accuracy of the simulator is fairly improved by these modifications.

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This paper describes a method for achieving novel appearances of a given face that can create intended impressions on observers. A morphable 3D model of the human face is developed to describe the variations in appearance while also using a small number of parameters. To find the physical parameters of the 3D objects that might strongly contribute to their visual impressions, the impression ratings obtained for learning samples are computationally investigated. Based on the quantification of higher-order impressions by the Semantic Differential (SD) method, the visual impression of the face can be transformed by manipulating the parameters defined in the morphable 3D model. The ability of the proposed method to transform impressions is confirmed by the paired comparison method.

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In recent years, many line drawing algorithms have been proposed for 3D shape depiction. One common drawback is that these algorithms draw only part of the necessary lines for fully depicting the shape. Cole et al.¹⁾ have shown that these algorithms can be complementary to each other. Based on that, in this paper, we combine the previous algorithms to produce better line drawings of 3D objects. By directly superposing multiple line drawing algorithms, however, there is a risk of generating too many unnecessary lines, especially in regions where many lines are located near to each other, making them to appear over-sketched. To solve this problem, we define an attribute called “importance” for all points on each line. The importance describes which lines should be drawn in preference. In addition, we determine the width of the lines based on the number of lines in their neighborhood. Our algorithm runs on GPU, achieving real-time speed. From experimental results, our method avoids drawing excessive lines while conveying the shapes effectively.

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Creating a 3D model of a human face from an image sequence remains an important problem in the fields of computer vision and computer graphics. We propose a method based on a factorization algorithm; it automatically constructs a 3D face model from an image sequence that contains turntable motion of the face as captured by a monocular camera. Our proposal uses multiple Active Appearance Models for feature tracking to avoid manual operations and to recover the 3D shape of the whole face. In contrast to previous methods, our approach requires no 3D generic model and can obtain the user's individual 3D face shape. Experiments conducted on real image sequences demonstrate the effectiveness of the proposed method.

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In this paper, we propose a new type of deform map where both the close and the distant view are expressible. When we use a 2D ordinal map of a local area, we sometimes want to know some information of the outside, i.e. the direction of a far city or the shape of far mountains from the local area. To realize this demand, a new expression is proposed. The local information is drawn in the central area of the map by top view parallel projection like 2D ordinal maps. The information of the far cities and mountains are drawn in the surrounding area by overhead or side view projection so that the direction of cities and the shape of mountains are expressed. To establish smooth connection of both areas, a novel multi aspect projection technique is developed. Several rendering techniques, such as blending of multiple map textures, LOD control, and contour enhancement of mountains, are combined to obtain comprehensible result within interactive time.

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In this paper, a method to enable people to experience “Chinkin” in the virtual space is proposed. Chinkin is a traditional artistic technique in Japan and some Asian countries to draw designs on lacquer ware with fine lines and dots, and it was widely used to produce Daimyo's utensils in the Edo period during the 17th and the 19th century. The author develops a virtual Chinkin system based on the virtual sculpting method which is an interactive CG creating method developed by the author. The real Chinkin consists of some processes and each process is realized by virtual carving: an interactive deformation of solids, and virtual painting: an interactive generation of a 3D texture map in the virtual space. Improvement in a rendering method is also given for more useful operation. In this system, the user can experience each process of the Chinkin technique in the virtual space and can create virtual sculptures ornamented with Chinkin designs as CG. Both the operation and the result are similar to the real ones and it would be useful for introduction, education and preservation of the traditional Chinkin technique.

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We propose an efficient method based on physical laws to model phenomena near the surface of the sun, which is known as the solar photosphere. In the field of astronomy, some physical models have been developed to simulate the sun's turbulence. Most of the previous models are difficult to be applied in the making of CG images since they require a considerable amount of time even when using a supercomputer. The subject of our research is the visual simulation of the phenomena observed above the photosphere, namely solar prominences, because these are characteristic phenomena of the sun that can greatly influence the visual impact in movies and games. The sun is mainly composed of ionized plasma, and its behavior can be treated as a fluid. However, unlike gas, the plasma fluid is influenced by the magnetic field. Thus, magnetic field calculations are needed to calculate the plasma behavior. We use the magnetohydrodynamics (MHD) equations to simulate the behavior of plasma. We propose a new method which can simulate a prominence in a practical computation time. The computation cost is reduced by simplifying the phenomena inside the sun: we only consider the phenomena after the solar prominence erupts because the phenomena before the eruption dose not manifest itself in a visual way. To render the simulation results, we emulate an observation method that extracts the specific spectrum emission from the solar plasma.

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We propose a visual appearance simulation method for exhibited objects such as direction boards considering both eyesight and visual angles of viewers. Our method consists of two steps: optical simulation step and neural simulation step. In optical simulation step, first, the visual angle of the actual exhibited objects and of the images on computer monitors are matched. Then, we generate blurred image to simulate viewers' eyesight by using Gaussian filter. In neural simulation step, we simulate image contrast enhancement due to lateral inhibition by applying a convolution filter with DOG distribution. Appropriate parameters of both filters are based on experimental measurements, which are corresponding to viewers' eyesight. Our method can simulate visual appearance of various exhibited objects which is viewed from arbitrary distance with arbitrary eyesight.

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Objective evaluation methods of visual induced motion sickness (VIMS) caused by interactive video such as computer game is studied to clarify the relation between VIMS and image motion components. We focus on time-variant biosignal indices related autonomic nervous activity, and estimate availability of two indices called ΔI_LF/HF based on LF/HF ratio and triggerpoints from heart rate signals. As a result of experiment by 20 subjects, the biosignal indices have positive correlation with the global motion of video in case of non-interactive video, whether unpleasant subjective score is low or high. In case of interactive video, on the other hand, both subjective score and triggerpoints by biosignal decrease compare to that of non-interactive video, and ΔI_LF/HF indices tendency depends on the operation type of video in case of interactive video. These results suggest that triggerpoints indices are possible to use for evaluation of VIMS related by GMV, and ΔI_LF/HF indices are possible to use unconscious VIMS effect in ANA level caused by video motion and operation rather than subjective unpleasant sensation.

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多様なフィルタを用いてボトムアップに生成された特徴マップ群から，それを統合した二次元平面上の特徴の多様性の高さを示すSaliency マップを計算する計算論的概念が提案されている． そこではフーリエ変換や回転フィルタなどの一般的なフィルタを用いて特徴が抽出されている． ヒトの視覚のフィルタには様々なフィルタが観測されており，そこで使用するフィルタがSaliency マップに多大に影響する． それに対して本稿では，ヒトの視覚にあると考えられる一般的なフィルタを用いるのではなく，観測画像に応じて自己組織的に生成するフィルタを用いてSaliencyマップを生成する手法を提案する． そのためにICA (Independent Component Analysis) 基底推定の概念をSaliency マップを生成するモデルに導入する． 格子配置の入力にフィルタをかけるのが一般的である一方で，受容細胞の配置は一般に格子上に整然と配置されていない． このような非均一な配置をしている受容野に対して計算できるフィルタを観測のみから自己組織的に生成できるように拡張する． 特にSaliencyマップを生成する上で重要な色や動きに関する生体が受け取っている情報を，受容細胞が受け取れるようモデル化する． そのためICA基底推定を色や動きの識別に必要な多次元に拡張する． ここで提案するICA基底推定によるSaliencyマップを生成する初期視覚モデルを実際にいくつかの画像に適用し，その有効性を示す．

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This paper introduces a new class of CFA interpolation algorithm. Conventional CFA interpolation methods usually apply a directional filtering in horizontal-, vertical-, or omni-direction even if edge runs in diagonal direction. We, then, invent a similarity based filtering using a local map called unified high-frequency (UHF) map. This new technique enables flexible filtering masks so as to be able to deal with edges of any direction such as diagonal edges. It is confirmed through experiments that the proposed algorithm outperforms state-of-the-art methods in terms of PSNR and subjective quality. In addition, the proposed algorithm is comparable to, or less expensive than the state-of-the-art methods regarding the resource consumption.

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オプティカルフローは動画像における連続する2フレーム間の画素ごとの動きベクトルである．本稿は輝度変化にロバストで高速なオプティカルフロー推定アルゴリズムを提案する．輝度変化量を差分平均により求め，時間輝度勾配を補正し，ロバスト化を図る．初期値設定法，階層処理法，ウィンドウサイズの最適化により処理の高精度化と高速化を図る．シミュレーションの結果，輝度変化を加えた場合の平均角度誤差は18.65°から4.29°に大きく改善され，ロバスト性を確認した．輝度変化を加えず精度を同程度とした場合のCPU実行時間は従来の15%となり，高速性を確認した．更に本アルゴリズムに基づく専用回路構成を提案し，FPGA実装する．提案回路は従来回路より輝度変化にロバストなうえに，同程度の精度とスループット性能を仮定したとき，動作周波数が20%，面積が45%未満，電力が9%未満に削減される．本回路は実時間画像認識や画像再構成に応用可能である．

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本稿では遺伝的アルゴリズム(GA)を用いた類似文字識別のための新しい特徴選択法を提案する．特徴は染色体に対応付けられ，認識に使用される特徴には“1”が，使用されない特徴には“0”が割り当てられる．提案手法は学習データの識別率があらかじめ定められた基準を超える遺伝子のみを予備選択し，その遺伝子に対して特徴数の減少比を適応度として親遺伝子を決定し，世代が進むに従い“1”をとる特徴を減少させていく機構を持つ．この機構により，識別率を維持しつつ認識に使用する特徴数を減少させることが可能となる．類似文字に対する識別実験において，提案手法はF比を用いる手法に比べて少ない特徴数で高い識別率を得た．また，特徴からその発生源の画素を表示する特徴可視化の手段によって，GAは人間が識別に用いていると推察される字形的差分を自動で獲得している様子を確認した．これらにより提案手法の有効性を確認した．

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理想的な投票技術では，匿名性，大規模実施の可能性，開票スピードと正確性が要求される．電子投票はコンピュータ技術の進歩で次世代の投票の形として期待されている．電子投票を選挙参加者に受け入れてもらうためには，投票の秘匿性の維持と開票作業が厳正に行われていることを参加者に納得させることが重要である．本稿は，使い捨てのコードブックに選挙用紙画像を利用して，秘密鍵および選挙情報の交換手段を提供し，再検証可能な投票暗号化方法を提案した．本稿では，RSAおよびMD5のアルゴリズムを利用して選挙管理機構と投票者のブラインド署名と秘密鍵の交換を選挙画像の電子透かし技術で実現し，本提案手法の有効性とロバスト性を実験によって示した．

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複数のWebカメラのリアルタイム実写入力による， パーソナルコンピュータ1台を使ったマルチタスク機能で， 二次元高速フーリエ変換（2D-FFT）を用いたキノフォーム型計算機合成ホログラフィックステレオグラム （キノフォーム型CGHS：Kinoform Type Computer Generated Holographic Stereogram）作成の検討を行った．

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緊急的な通報をろう者へ迅速，かつ的確に伝達するシステム構成の基礎検討として，ろう者3名の手話・日本語二言語緊急通報読み取り実験から得られた視線データを解析し，対象者個々人の読み取り行動（注視特性）を議論する．3名の対象者は，二つの通報が分離しているときは特定の通報領域へ注視が偏る．しかし，通報領域に重なりがある場合は，重なり領域への注視が多くなる傾向がある．また，注視時間だけからは必ずしも通報の読み取りの安定さは判断できないこともわかる．これらの解析結果は対象者の読み取りの多様性を示している．通報を対象者一人ひとりに，迅速，かつ的確に伝達するという緊急通報の役割達成には，個人特性の十分な検討と考慮とが必要なことを示唆している．更に，二言語緊急通報が有効に機能を果たすためにどのような検討が必要か，その課題群についても述べる．

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本稿では，2010年9月10～12日に開催された第10回ビジュアル情報処理研究合宿(以下，本合宿)の開催結果を報告する．本合宿は『学生の学生による学生のための合宿』であり，学生同士での研究についての議論の場の提供と，大学の枠を超えたネットワークの形成を目的として，全国の学生有志により企画・運営が行われている．特に本年度は，『きっかけ』というキーワードを合宿のテーマにかかげ，参加者に対して，研究や就職に対する新しい発見や考え方が得られるような合宿を目指し，目玉の企画として，短時間で問題を解決するきっかけとなるグループディスカッションや，学生の今後の研究や就職について意見交換するための教員・社会人への質問会を実施した．アンケート結果では，参加者の9割近くから合宿は有意義なものであったとの回答が得られた．

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