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Recently, several methods for foreground segmentation from moving camera have been proposed. A trajectory-based method is one of typical approaches to segment video frames into foreground and background regions. The method obtains long term trajectories from entire of video frame and segments them by learning pixel or motion based object features. However, it often needs large amount of computational cost and memory resource to maintain trajectories. We present a trajectory-based method which aims for real-time foreground segmentation from moving camera. Unlike conventional methods, we use trajectories which are sparsely obtained from two successive video frames. In addition, our method enables using spatio-temporal feature of trajectories by introducing case-based approach to improve detection results. We compare our method with previous approaches and show results on challenging video sequences.

Background modeling and subtraction is an essential task in video surveillance applications. Most traditional studies use information observed in past frames to create and update a background model. To adapt to background changes, the background model has been enhanced by introducing various forms of information including spatial consistency and temporal tendency. In this paper, we propose a new framework that leverages information from a future period. Our proposed approach realizes a low-cost and highly accurate background model. The proposed framework is called bidirectional background modeling, and performs background subtraction based on bidirectional analysis, i.e., analysis from past to present and analysis from future to present. Although a result will be output with some delay because information is taken from a future period, our proposed approach improves the accuracy by about 30% if only a 33-millisecond of delay is acceptable. Furthermore, the memory cost can be reduced by about 65% relative to typical background modeling.

Current object-recognition algorithms use local features, such as scale-invariant feature transform (SIFT) and speeded-up robust features (SURF), for visually learning to recognize objects. These approaches though cannot apply to transparent objects made of glass or plastic, as such objects take on the visual features of background objects, and the appearance of such objects dramatically varies with changes in scene background. Indeed, in transmitting light, transparent objects have the unique characteristic of distorting the background by refraction. In this paper, we use a single-shot light field image as an input and model the distortion of the light field caused by the refractive property of a transparent object. We propose a new feature, called the light field distortion (LFD) feature, for identifying a transparent object. The proposal incorporates this LFD feature into the bag-of-features approach for recognizing transparent objects. We evaluated its performance in laboratory and real settings.

Object detection is an important task for computer vision applications. Many researchers have proposed a lot of methods to detect the objects through the background modeling. Most of previous approaches model the background independently for each pixel and detect foreground objects based on it. Then, it is difficult for the background model to deal with illumination changes, which cause significant intensity changes as in the case that a foreground object appears. To solve this problem, in this paper, we propose a new background model considering the similarity in the intensity changes among pixels. In particular, we classify all the pixels into several clusters based on the similarity of their intensity changes. Then, focusing on each cluster, we can easily identify whether the significant intensity changes are caused by foreground objects or illumination changes. This is because, if the illumination changes, most of the pixels belonging to the same cluster exhibit the similar intensity changes.

We present a robust background model for object detection and report its evaluation results using the database of Background Models Challenge (BMC). Our background model is based on a statistical local feature. In particular, we use an illumination invariant local feature and describe its distribution by using a statistical framework. Thanks to the effectiveness of the local feature and the statistical framework, our method can adapt to both illumination and dynamic background changes. Experimental results, which are done thanks to the database of BMC, show that our method can detect foreground objects robustly against background changes.

A moving object or camera causes motion blur in a conventional photograph, which is a fundamental problem of a camera. In this research, we propose to code a motion-invariant blur using a programmable aperture camera. The camera can realizes virtual camera motion by translating the opening, and as a result, we obtain a coded image in which motion blur is invariant with the object velocity. Thereby, we recover motion blurs without estimation of the motion blur kernels or knowledge of the object speeds. We model the projection of the programmable aperture camera, and also demonstrate that our proposed coding works for a prototype camera.

We propose an intuitive operation based information retrieval system “Clickable Real World (CRW)”. If a user which uses this system takes a picture of a landmark in the world, some related information is displayed on a smartphone. One of the key research issues is how to estimate appropriate keywords in order to retrieve information related to the target. Our strategy utilizes a lot of training samples, which consist of images, tags and geolocation where the image was taken, shared on the Web (such as flickr and Picasa). Then, a keyword table is created based on the consistency of geolocation and visual feature. We developed a prototype version of CRW on a smartphone, and conducted a field experiment in Kyoto city, Japan.

Initially, the initiation mechanism for the copolymerization of 1,3,5-trioxane (TO) and ethylene oxide proposed the formation of 1,3-dioxolane from the reaction of ethylene oxide with formaldehyde, and this mechanism was believed plausible for a long time. Recently, we carefully studied the bulk copolymerization of TO and ethylene oxide using boron trifluoride-dibutyl ether as the initiator. Two novel cyclic formals, 1,3,5,7-tetraoxacyclononane (TOCN) and 1,3,5,7,-10-pentaoxacyclododecane (POCD), from the initiation reaction of the copolymerization of TO and ethylene oxide were isolated and identified. From this discovery, we proposed a new initiation mechanism for the copolymerization of TO and ethylene oxide. Ethylene oxide reacts directly with TO to form TOCN and POCD. From TOCN, 1,3,5-trioxepane (TOXP) is formed, and from TOXP, 1,3-dioxolane is formed.

In this paper, we propose a method combining visual local features and depth image information to recognize cooking gestures. We employ the feature calculation method[2] which used extended FAST detector and a compact descriptor CHOG3D to calculate visual local features. We pack the local features by BoW in frame sequences to represent the cooking gestures. In addition, the depth images of hands gestures are extracted and integrated spatio-temporally to represent the position and trajectory information of cooking gestures. The two kinds of features are used to describe cooking gestures, and recognition is realized by employing the SVM. In our method, we determine the gesture class for each frame in cooking sequences. By analyzing the results of frames, we recognize cooking gestures in a continue frame sequences of cooking menus, and find the temporal positions of the recognized gestures.

This paper presents the largest inertial sensor-based gait database in the world and its application to a statistically reliable performance evaluation for gait-based recognition problem. Whereas existing gait databases include at most a hundred subjects, we construct a much larger gait database for both accelerometer and gyroscope which includes 736 subjects (382 males and 354 females) with ages ranging from 2 to 78 years. Because a sufficiently large number of subjects for each gender and age group are included in this database, we can analyze the dependence of gait recognition performance on gender or age groups. The results with the latest existing recognition method provide several novel insights, such as the trade-off of gait recognition performance among age groups derived from the maturity of walking ability and physical strength. Moreover, the evaluation for the recognition performance improvement with a larger number of subjects was reliably confirmed in the experiments. As for sensor data type, acceleration is better than angular velocity for gait recognition performance. Compared to unnormalized distance (such as Euclidean distance), normalized distance (such as normalized cross correlation-based distance) works significantly better for angular velocity.

The growth of photo-sharing website such as Flickr and Picasa enables us to access the billions of images easily. Recent years, many researchers leverage such photo-sharing site to tackle the image annotation problem. The aim of the image annotation is to give a proper label to an unknown image. Generally, image features and label features are used to acquire the relationship between them. Meanwhile, we use not only such image and label features but also geolocation which indicate the information where the image was taken. We formulate the image annotation problem as two important issues; image-based labeling and label-based localization. The former issue is to estimate a proper label from a given image. The latter is the issue to estimate the location from the label. Our approach combine these two estimation strategies. We conducted some experiments and found that our approach outperformed the traditional approach.

In this paper, we propose a method of inertial sensor-based gait authentication by inter-period phase registration of an owner's gallery. In spite of the importance for gait authentication of constructing a gallery of phase-registered gait patterns, previous implementations just relied on simple methods of period detection based on heuristic knowledge such as local peaks/valleys or local auto-correlation of the gait signals. Consequently, we propose to improve a gait gallery by incorporating a phase registration technique which globally optimizes inter-period phase consistency in an energy minimization framework. However, the previous phase registration technique suffers from a phase distortion problem due to ambiguities in the combination of a periodic signal function and a phase evolution function. We present a linear phase evolution prior to constructing an undistorted gait signal for better matching performance. Experiments using real gait signals from 32 subjects show that the proposed methods outperform the latest methods in the field.

We propose a new approach for early gesture recognition. Early gesture recognition is a method to recognize sequential posture patterns at their beginning parts. Using early gesture recognition, we can reduce the delay and increase the interactivity of the system. The key issue of early recognition problem is how to recognize the beginning part of gesture. Generally, a reference gesture consists of a sequence of postures. Therefore, to realize early recognition we have to select beginning parts of the posture sequences. In this paper, we propose a method to obtain such beginning parts of the posture sequences, and demonstrate its effectiveness through some experiments.

We propose a new method of background modeling for object detection. Many background models have been previously proposed, and they are divided into two types: "pixel-based models" which model stochastic changes in the value of each pixel and "spatial-based models" which model a local texture around each pixel. Pixel-based models are effective for periodic changes of pixel values, but they cannot deal with sudden illumination changes. On the contrary, spatial-based models are effective for sudden illumination changes, but they cannot deal with periodic change of pixel values, which often vary the textures. To solve these problems, we propose a new probabilistic background model integrating pixel-based and spatial-based models by considering the illumination fluctuation in localized regions. Several experiments show the effectiveness of our approach.

The range of scene depths that appear focused in an image is known as the depth of field (DOF). Conventional cameras are limited by a fundamental trade-off between depth of field and signal-to-noise ratio (SNR). For a dark scene, the aperture of the lens must be opened up to maintain SNR, which causes the DOF to reduce. Also, today's cameras have DOFs that correspond to a single slab that is perpendicular to the optical axis. In this paper, we present an imaging system that enables one to control the DOF in new and powerful ways. Our approach is to vary the position and/or orientation of the image detector during the integration time of a single photograph. Even when the detector motion is very small (tens of microns), a large range of scene depths (several meters) is captured, both in and out of focus. Our prototype camera uses a micro-actuator to translate the detector along the optical axis during image integration. Using this device, we demonstrate four applications of flexible DOF. First, we describe extended DOF where a large depth range is captured with a very wide aperture (low noise) but with nearly depth-independent defocus blur. Deconvolving a captured image with a single blur kernel gives an image with extended DOF and high SNR. Next, we show the capture of images with discontinuous DOFs. For instance, near and far objects can be imaged with sharpness, while objects in between are severely blurred. Third, we show that our camera can capture images with tilted DOFs (Scheimpflug imaging) without tilting the image detector. Finally, we demonstrate how our camera can be used to realize nonplanar DOFs. We believe flexible DOF imaging can open a new creative dimension in photography and lead to new capabilities in scientific imaging, vision, and graphics.

"Clickable Real World" is a new methodology to retrieve real-time real-world information from the web. The key point is that the query here is the name and the attributes of a given landmark, which is given by taking a picture of the landmark by a mobile phone camera. The user can feel to directly click the landmark in front of him/her by the shutter clicks. One of the great advantages of our approach is to use open image database such as Flickr, Picasa, or so on, to identify a landmark. Images on such open databases are automatically updated and some proper keywords are given by photographers in the world. Therefore, we need not prepare reference images which are required to identify a landmark. In addition, a matched image might have proper labels which indicate the landmark. In this paper, we will explain the overview of Clickable Real World and report some experimental results.

A new reaction between 1,3,5-trioxane and ethylene oxide has been observed and a novel cyclic formal, which is the reaction product of 1 equiv. of 1,3,5-trioxane and 1 equiv. of ethylene oxide, has been isolated and identified.

We propose a new robust estimator for parameter estimation in highly noisy data with multiple structures and without prior information on the noise scale of inliers This is a diagnostic method that uses random sampling like RANSAC, but adaptively estimates the inlier scale using a novel adaptive scale estimator The residual distribution model of inliers is assumed known, such as a Gaussian distribution Given a putative solution, our inlier scale estimator attempts to extract a distribution for the inliers from the distribution of all residuals This is done by globally searching a partition of the total distribution that best fits the Gaussian distribution Then, the density of the residuals of estimated inliers is used as the score in the objective function to evaluate the putative solution The output of the estimator is the best solution that gives the highest score Experiments with various simulations and real data for line fitting and fundamental matrix estimation are carried out to validate our algorithm, which performs better than several of the latest robust estimators.

アセタール樹脂の新製造技術を開発した。第一は,メチラールを酸化することにより高濃度のホルマリンを得る新技術を開発した。メタノールの酸化では,ホルムアルデヒド1molに対して水が1mol生成するが,メチラールの酸化では3molのホルムアルヒドに対て,水は1molである。従って,工業的にはメタノール酸化法では55%のホルマリンが得られるのに対してメチラール酸化では70%以上の高濃度のホルマリンを得ることができる。第二は,この高濃度ホルマリンから高度に精製されたホルムアルデヒドを無水酢酸を分子量調節剤,もしくは末端封鎖剤としての作用の存在下で重合させると,重合時に末端が封鎖されたポリマーが得られる。第三に,高濃度ホルマリンはトリオキサンの生成を促進する。高度精製トリオキサンをエチレンオキシドとの共重合に際して末端封鎖剤の存在下で重合すると,末端が封鎖された安定なポリマーが得られる。共重合の開始反応において,二つの新規化合物である1,3,5,7-テトラオキサシクロノナン(TOCN)と1,3,5,7,10-ペンタオキサシクロドデカソ(POCD)が単離され,新しい開始反応機構が提案された。第四に,活性水素を有する潤滑性機能性ポリマーの存在下でホルムアルデヒドを重合させることにより,世界で最初のアセタールブロックコポリマーを工業化した。このアセタールブロヅクコポリマーは優れた潤滑性能を示した。

Serological survey of Rhodococcus equi infection in horses in Hokkaido was performed using ELISA. Of 2,879 horse sera, 318 (11.0%) gave antibody-positive (OD greater than or equal to 0.3) reactions. The antibody-positive rate of female was significantly higher (p less than 0.01) than that of male, and no statistical difference between Anglo-Arab and thoroughbred was detected in the antibody-positive rate. The maximum antibody-positive rate (27.1%) was shown at 14 years of age. The antibody-positive rates on the 160 farms were found to vary widely from 0 to 78.9%. A significant difference (p less than 0.01) in the antibody-positive rate was detected among horse farms. It was elucidated that 100 (62.5%) out of 160 horse farms had an antibody-positive horse. These results indicate that R. equi was widespread on horse farms, and the level of environmental contamination with R. equi differed among horse farms.

(2000). Super-resolution for an omnidirectional vision sensor. Advanced Robotics: Vol. 14, No. 5, pp. 427-429.

Although RANSAC is the most widely used robust estimator in computer vision, it has certain limitations making it ineffective in some situations, such as the motion estimation problem, in which uncertainty on the image features changes according to the capturing conditions. The greatest problem is that the threshold used by RANSAC to detect inliers cannot be changed adaptively; instead it is fixed by the user. An adaptive scale algorithm must therefore be applied in such cases. In this paper, we propose a new adaptive scale robust estimator that adaptively finds the best solution with the best scale to fit the inliers, without the need for predefined information. Our new adaptive scale estimator matches the residual probability density from an estimate and the standard Gaussian probability density function to find the best inlier scale. Our algorithm is evaluated in several motion estimation experiments under varying conditions and the results are compared with several of the latest adaptive-scale robust estimators.

Image based modeling methods has been well studied for generating a 3D model from an image sequence. Most of them require redundant and huge spatio-temporal images for estimating a scene depth. It is not good characteristic for taking a higher resolution of texture. A route panorama is a continuous panoramic image along a path. It is suitable for modeling large environments such as a city or town. The panorama captured by a line scan sensor also has advantage for capturing higher resolution easily. In this paper, we propose a method for depth estimation from the panorama. The route panorama has color drifts that correspond to the distances of captured objects. We use these color drifts to estimate the depth of an image. The proposed method detects the color drift by window matching using belief propagation. It also uses a Gaussian pyramid to stabilize the estimation and decrease its computation cost. We confirmed that the proposed method estimated depth maps from a single high-resolution panorama in experiments.

ベンゼンの液相部分水素化反応機構の解析を行った。反応はRu触媒,助触媒(酸化亜鉛) ,および水の存在下,ベンゼン-d6を用いて行い,生成物中の重水素量を詳細に比較した。触媒上では吸着基質であるオレフィソと,気相水素もしくは水から供給される解離吸着水素との間にC-D～H交換反応が発生している。この交換反応は助触媒を添加した場合のシクロヘキセンの生成過程で特に顕著であった。また,触媒上でシク導ヘキサンが生成する過程は複雑で1単鮪な水素導入過程とは別に,シク糠ヘキセンから脱離した水素により生成した解離吸着水素による水素化の過程が存在することが明らかとなった。反応の選択性は助触媒の添加により大きく向上した。これは助触媒である亜鉛化合物が,触媒上での水素化中間体を安定化してシクロヘキサンへの水素化を抑制し,シクロヘキセンとして脱離する確率を高めること,およびシクロヘキセソの再吸着を阻害することによると推定された。

Camera ego-motion consists of translation and rotation, in which rotation can be described simply by distant features. We present a robust rotation estimation using distant features given by our compound omnidirectional sensor. Features are detected by a conventional feature detector, and then distant features are identified by checking the infinity on the omnidirectional image of the compound sensor. The rotation matrix is estimated between consecutive video frames using RANSAC with only distant features. Experiments with various environments show that our approach is robust and also gives reasonable accuracy in real-time.

Many omnidirectional vision sensors based on convex mirrors have been proposed for observing a 360 degrees field of view. Some have a single viewpoint using a hyperboloidal or parabolic mirror, others have a constant resolution property. Until now, there have not been any that have had both these properties. In this paper, we propose an omnidirectional vision sensor that has both properties; that is, a single viewpoint and a constant resolution. The proposed omnidirectional sensor uses two mirrors, which improves the degree of freedom of the design for satisfying each property. We discuss optimization of the design in terms of geometry and optics.

It is desirable to engineer a small camera with a wide field of view (FOV) because of current developments in the field of wearable cameras and computing products, such as action cameras and Google Glass. However, typical approaches for achieving wide FOV, such as attaching a fisheye lens and convex mirrors, require a trade-off between optics size and the FOV. We propose camera optics that achieve a wide FOV, and are at the same time small and lightweight. The proposed optics are a completely lensless and catoptric design. They contain four mirrors, two for wide viewing, and two for focusing the image on the camera sensor. The proposed optics are simple and can be simply miniaturized, since we use only mirrors for the proposed optics and the optics are not susceptible to chromatic aberration. We have implemented the prototype optics of our lensless concept. We have attached the optics to commercial charge-coupled device/complementary metal oxide semiconductor cameras and conducted experiments to evaluate the feasibility of our proposed optics.

Many omnidirectional vision sensors using a convex mirror have been proposed for observing a 360 degrees field of view. Some of them have a single viewpoint using a hyperboloidal or parabolic mirror, some of the others have a constant resolution property. Until now, there have not been any that have had both these properties. In this paper, we propose an omnidirectional vision sensor that has both a single viewpoint and a constant resolution. The proposed omnidirectional sensor uses two mirrors, which improves the degree of freedom of the design for satisfying each property. We introduce three practical settings of constant resolution; angular constant, horizontal constant and vertical constant resolutions.

In accordance with advances in camera technology, the requirement of high-quality video has greatly increased. Among the factors required for high-quality video are a high-resolution and a high frame rate. However, the limitation of the pixel transfer rate restricts compatibility of a high-resolution and a high frame rate in commercial camera. We propose a dual-sensor camera that consists of two cameras: one with a high-resolution and a low frame rate and the other with a low-resolution and a high frame rate. The system is capable of capturing two different image sequences: high-resolution images and high-frame-rate images. A sensor calibration for the dual-sensor camera is also proposed.

This paper proposes a new algorithm for Simultaneous Localization and Mapping (SLAM) with omnidirectional stereo vision. In our approach, stereo matching is solved efficiently by using the estimated spatial information of the environment and robot motion. The use of two EKF (Extended Kalman Filter) estimators brings about a more reliable robot trajectory and a better map of the environment with more landmarks. The first estimator (a binocular estimator) mostly focuses on the robot trajectory; the second estimator (a monocular estimator) is devoted to the map building. Reliably matched landmarks are entered into the first estimator to establish the reliable robot position and some of the landmark positions. Other landmarks, which have more uncertainty of stereo combination or are observed by only one camera, are passed to the second estimator to establish their positions. This structure results in more precise estimation of robot trajectory and a map of the environment with more landmarks.

A number of applications in many fields, including virtual reality, digital archiving, etc., now require the capturing of large fields of view (FOV) and high-resolution images. Recently, rotating line cameras have been used for high-resolution and wide field of view panorama imaging. Some are equipped with a fish-eye lens and can observe a full spherical panorama image. We proposed a calibration method for rotating line cameras, using a spherical imaging model for the application of a full spherical panorama image. For the calibration, the proposed method uses 3D line segments that variously exist in man-made environments.

We propose a novel strategy to obtain a high spatio-temporal resolution video. To this end, we introduce a dual sensor camera that can capture two video sequences with the same field of view simultaneously. These sequences record high resolution with low frame rate and low resolution with high frame rate. This paper presents an algorithm to synthesize a high spatio-temporal resolution video from these two video sequences by using motion compensation and spectral fusion. We confirm that the proposed method improves the resolution and frame rate of the synthesized video.

This paper presents a novel algorithm for obtaining a high spatio-temporal resolution video from two video sequences. These sequences are high resolution with low frame rate and low resolution with high frame rate. To this end, we introduce a dual sensor camera that can capture these sequences with the same field of view simultaneously. The proposed method observes motion information through the video with high frame rate. Moreover, the method conducts both motion compensation for the high resolution sequence and image fusion in the wavelet domain. We confirmed that the proposed method improves the resolution and frame rate of the synthesized video.

Many applications have used a Head-Mounted Display (HMD), such as in virtual and mixed realities, and tele-presence. The advantage of HMD systems is the ease of feeling a 3D world in the display of animation or movies. However, the field of view (FOV) of commercial HMD systems is too narrow for feeling immersion. The horizontal FOV of many commercial HMDs is around 60 degrees, significantly narrower than that of humans. In this paper, we propose a super wide field of view head-mounted display consisting of an ellipsoidal and a hyperboloidal curved mirror. The horizontal FOV of the proposed HMD is 180 degrees and includes the peripheral view of humans. It increases reality and immersion of users. As well, the central region (60 degrees) of the FOV can measure 3D distances using stereoscopics.

Many applications have used a Head-Mounted Display (HMD), such as in virtual and mixed realities, and tele-presence. The advantage of HMD systems is the ease of feeling a 3D world in the display of animation or movies. However, the field of view (FOV) of commercial HMD systems is too narrow for feeling immersion. The horizontal FOV of many commercial HMDs is around 60 degrees, significantly narrower than that of humans. In this paper, we propose a super wide field of view catadioptrical head-mounted display consisting of an ellipsoidal and a hyperboloidal curved mirror. The horizontal FOV of the proposed HMD is 180 degrees and includes the peripheral view of humans. It increases reality and immersion of users. As well, the central region (60 degrees) of the FOV can measure 3D distances using stereoscopics.

In this paper, we propose a tele-operation system with a super wide field of view (FOV). Our tele-operation system has an omnidirectional image sensor for capturing a panoramic image and a personal spherical screen display for projecting a wide angle image. Our first contribution is the application of our system to navigate the mobile robot by tele-operation and evaluate the efficiency of wide angle image. Our second contribution is the proposal of super wide FOV. Generally, FOVs of a common display system and a HMD system are restricted and it is unable to see the outer of FOV of a common display system. The idea of super wide FOV is a nonlinear transformation from the input image to the display. Therefore, the operator can look behind even if the display is not the paranorama display such as the cylindrical large screen and the CAVE system.

Recently, many applications in virtual reality and robotics require to create virtual environment from a real scene. A catadioptric omnidirectional image sensor composed of a convex mirror can observe a 360-degree field of view at once. It is useful for modeling a man-made environment such as a room, a corridor and a building, because the landmarks around the sensor can be taken and tracked by its large field of view. However, the angular resolution of the omnidirectional image is low owing to capturing the large field of view. Therefore, the resolution of texture patterns of each surface on the generated 3D scene model is not enough for monitoring details. To solve this problem, we propose a high-resolution scene texture generation method that combines an omnidirectional image sequence using image mosaic and super-resolution techniques.

Publisher Summary This chapter investigates the catalytic performance in partial hydrogenation of benzene over supported ruthenium catalysts prepared from Ru 3 (CO) 12 and RuCl 3 . The effect of various supports and Ru–M bimetallic catalysts are tested for this reaction. The ruthenium particle size of 5%Ru/ZrO 2 catalysts prepared from Ru 3 (CO) 12 and RuCl 3 determined from H 2 adsorption, X-ray diffraction (XRD), and transmission electron microscope (TEM); and the results of partial hydrogenation of benzene using these catalysts are presented in the chapter. Particle size of each catalyst obtained from H 2 adsorption, XRD, TEM was in good agreement. H 2 adsorption studies of Ru 3 (CO) 12 -derived catalyst showed high dispersion and no clear peaks due to ruthenium crystal were observed in XRD spectra. From TEM observation, the average particles size of Ru 3 (CO) 12 and RuCl 3 -derived catalysts were 2.0 and 4.8 nm, respectively. A H 2 –temperature-programmed desorption (TPD) spectrum of Ru 3 (CO) 12 -derived catalyst showed two major peaks with the maximum intensity in the middle and high temperature range, which could be due to the formation of well defined Ru species.

The authors describe an omnidirectional image sensor, called HyperOmniVision, that can observe a 360 degree field of view and can transformed an input image to a common camera image or a panoramic image easily. However, it has an intrinsic problem where the angular resolution of HyperOmniVision is lower than that of a conventional video camera. The authors propose a super-resolution method for HyperOmniVision, which fuses consecutive images obtained the by turning motion of HyperOmniVision. They discuss the optimization of both optics and processing by simulation results.

DFT calculations put forth theoretical grounds for a smooth reaction between methoxy and carbonate groups on the organotin template to afford dimethyl carbonate (DMC). The strong association of the...

Complete end-capping during the copolymerization of trioxane and ethylene oxide in the bulk polymerization state using boron trifluoride dibutyl ether as the initiator and methylal as the chain transfer agent was accomplished. By using highly purified trioxane as the starting material and by completely deactivating the catalyst residue, an almost completely end-capped polymer (degree of stability was over 99.5%) was obtained.

A new reaction between 1,3,5-trioxane and ethylene oxide has been observed and a novel cyclic formal, which is the reaction product of 1 equiv. of 1,3,5-trioxane and 1 equiv. of ethylene oxide, has been isolated and identified.

Many applications have used a Head-Mounted Display (HMD), such as in virtual and mixed realities, and tele-presence. The advantage of HMD systems is the ease of feeling a 3D world in the display of animation or movies. However, the field of view (FOV) of commercial HMD systems is too narrow for feeling immersion. The horizontal FOV of many commercial HMDs is around 60 degrees, significantly narrower than that of humans. In this paper, we propose a super wide field of view catadioptrical head-mounted display consisting of an ellipsoidal and a hyperboloidal curved mirror. The horizontal FOV of the proposed HMD is 180 degrees and includes the peripheral view of humans. It increases reality and immersion of users. As well, the central region (60 degrees) of the FOV can measure 3D distances using stereoscopics.

EDA complex formation between 2,4,7-trinitrofluorenone (TNF) and polyesters bearing pendant 9-carbazolyl groups was studied in ethylene dichloride. The formation constant (K) decreases with increasing length of the main chain repeating units separating pendant donor groups and with decreasing degree of polycondensation. In all cases, the values of K in polymeric systems are larger than those for the monomer model system by factors less than three. Thermodynamic parameters for complex formation were also determined. The general trend of the polymer effect is to increase − ΔH, while the entropy term is not much different from the monomer model system. The origin of polymer effects is interpreted as due not only to neighbouring group effects but also to remote group effects, and simultaneous participation of more than one carbazolyl group in complexing an acceptor molecule is considered. The results are compared with the EDA complex formation by ethylenic polymers and polyurethanes with pendant carbazolyl groups.

A polyurethane having pendant carbazolyl groups separated by four methylene groups was prepared and the EDA complex formation with 2,4,7-trinitrofluorenone (TNF) was studied in chloroform. EDA complexes of the polymer and the monomer model compound are spectroscopically indistinguishable. The formation constant (K) of the polymer complex is about equal to that of the monomer model compound in the oligomeric range whereas K increases with increasing molecular weight of the polymer. This trend of polymer effect is the same for the complex formation with other acceptors such as tetracyanoethylene (TCNE) and 1,3,5-trinitrobenzene (TNB). The formation of the polymer complex is entropically favoured although the negative enthalpy change is larger for the monomer model compound. The reasons are discussed.

Interpolymer EDA complex formation between polyesters bearing pendant carbazolyl groups and polyurethanes bearing pendant trinitrofluorenonyl groups was investigated in dioxane at 25°C. Complex formation depends on the degree of polycondensation (DP) as well as on structure matching of polymeric D and polymeric A. With increasing DP, the solubility of the D polymer-A polymer mixture trends to decrease. Even when the polymer complexes do not precipitate, the Ketelaar's plots do not always fall on a straight line. These phenomena were interpreted as due to higher order complex formation and/or dependence of the formation constant on the fraction of saturation. It was found that polymeric donor acceptor pairs in which the number of atoms in a repeating main chain unit are identical for D and A polymers form a stronger complex than other combinations. It was concluded that structure matching of an interacting pair is a favourable condition to form tight complexes as in the case of antigenantibody interactions.