The first of the trio Antarctic Survey Telescopes (AST3) has been deployed to Dome A, Antarctica in January
2012. This largest optical survey telescope in Antarctica is equipped with a 10k × 10k CCD. The huge amount of
data, limited satellite communication bandwidth, low temperature, low pressure and limited energy supply all
place challenges to the control and operation of the telescope. We have developed both the hardware and software
systems to operate the unattended telescope and carry out the survey automatically. Our systems include the
main survey control, data storage, real-time pipeline, and database, for all of which we have dealt with various
technical difficulties. These include developing customized computer systems and data storage arrays working at
the harsh environment, temperature control for the disk arrays, automatic and fast data reduction in real-time,
and building robust database system.
In this paper, a micro amperometric immunosensor based on Micro-Electro-Mechanical Systems technology for the
detection of Salmonella typhimurium (S. typhimurium) was constructed by immobilizing a polyclonal antibody (the
bio-molecular recognition element) onto the surface of polypyrrole(PPy) /staphylococcal protein A(SPA) modified Pt
electrode. Pyrrole doped with SPA was co-electropolymerized onto the working electrode surface by cyclic voltammetry
in 10 minutes for orientation-controlled immobilization of salmonella capture antibodies. S. typhimurium with the
concentration of 102cfu/ml could be detected by this immunosensor with a controllable and convenient manipulation to
effectively modify the sensing surface more rapidly with less consumption of reagent (10µL), which showed the good
property of the sensor. It is potential to develop a micro biosensor that can be used for convenient, accurate,
cost-effective and real-time sensing of pathogens in food products.
This paper proposes a method that using an electric field to improve the immobilization of analyte in an amperometric immunosensor. The amperometric immunosensor, which has a two-microelectrode system enclosed in a SU-8 reaction microwell, has been developed with MEMS technology for the detection of the human immunoglobulin (HIgG). Electric field has been applied above the working electrode by setting the appropriate potential between two electrodes to enable more antigen "IgG" to be assembled to the sensing interface with less time. The results demonstrate that the immunochemical incubation time spent on the immobilization of HIgG has been shortened, and the property of the immunosensor has been enhanced.
A micro plane amperometric immunosensor for the detection of human immunoglobulin G is fabricated on silicon
wafer based on Micro-Electro-Mechanical Systems (MEMS) technology. This microsensor is an electrochemical system
composed of two-electrode (working electrode and counter electrode) integrated with a micro reaction cell made of SU-8
photoresist. The sensitive area of the working electrode is only 1 mm2.
A new method for the orientation-controlled immobilization of antibody based on staphylococcal protein A (SPA) and
polypyrrole (PPy) is developed, which is fast, controllable and proper to microelectrode. PPy as a transition layer is first
electropolymerized at the sensing area of the working electrode. Then SPA is co-electropolymerized with PPy for further
orientedy immobilization of antibody. The electrodes modified by PPy and the coelectropolymer of PPy and SPA were
characterized by SEM. HIgG range from 5 ng/ml to 640 ng/ml can be detected by this immunosensor with less
consumption of reagent and acceptable reproducibility and stability.
A novel content-based image retrieval data structure is developed in present work. It can improve the searching
efficiency significantly. All images are organized into a tree, in which every node is comprised of images with similar
features. Images in a children node have more similarity (less variance) within themselves in relative to its parent. It
means that every node is a cluster and each of its children nodes is a sub-cluster. Information contained in a node
includes not only the number of images, but also the center and the variance of these images. Upon the addition of new
images, the tree structure is capable of dynamically changing to ensure the minimization of total variance of the tree.
Subsequently, a heuristic method has been designed to retrieve the information from this tree. Given a sample image,
the probability of a tree node that contains the similar images is computed using the center of the node and its variance.
If the probability is higher than a certain threshold, this node will be recursively checked to locate the similar images. So
will its children nodes if their probability is also higher than that threshold. If no sufficient similar images were founded,
a reduced threshold value would be adopted to initiate a new seeking from the root node. The search terminates when it
found sufficient similar images or the threshold value is too low to give meaningful sense. Experiments have shown that
the proposed dynamic cluster tree is able to improve the searching efficiency notably.
To improve the retrieval accuracy of content-based video retrieval systems, researchers face a hard challenge that is
reducing the 'semantic gap' between the extracted features of the systems and the richness of human semantics. This
paper presents a novel video retrieval system to bridge the semantic gap. Firstly, the video captions are segmented from
the video and then are transformed into text format. To extract the semantic information from the video streaming we
apply a text mining process, which adopts a cluster algorithm as a kernel, on the text format captions. On the other hand,
in this system, users are requested to comment on the video which they download from the system when they have
watched the video. Then we associate the users' comments with the video on the system. The same text mining process
is used to deal with the comment texts. We combine the captions of the video with the comments on the video to extract
the semantic information of the video more accurately. Finally, taking advantage of the comments and the captions of the
video, we performed experiments on a set of videos and obtained promising results.
Proc. SPIE. 5292, Human Vision and Electronic Imaging IX
KEYWORDS: Visual process modeling, Virtual reality, Data modeling, Solid modeling, Motion models, Human vision and color perception, Databases, Data processing, Vision-based navigation, Computer simulations
Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and
D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.
Object-order volume rendering algorithms play important part in many visualization applications for their excellent performances. Though many volume rendering algorithms have been proposed during the past two decades, most of them are image-order algorithms. Splatting, one of the classical object-order algorithms, suffers from several kinds of aliasing artifacts for inaccuracy reasons. A much accurate object-order volume rendering algorithm is presented in this paper. By defining a set of data structures to serve as two step reconstruction lookup tables, together with using a simple voxel traversal and resample strategy, the new algorithm can not only get rid of inaccuracy of traditional splatting, but also have the features including high cache hit rate, easy to implement of parallelism and high speedup from pre-processing.
This paper described the design of the DAVRS system. This system not only provides a 3D design environment for architects, but also realizes distributed collaboration between the designers through the internet. The DAVRS system used Java3D to construct virtual sense, XML to pocket sense controlling data, and Java MQ to transmit data. Moreover, a three-level distributed collaboration model is designed in order to confirm the safety of collaboration based on internet.
Volume rendering has been a key technology in the visualization of data sets from various disciplines. However, real-time volume rendering of large scale data sets is still a challenging field due to the vast memory, bandwidth and computational requirements. In this paper, to visualize small to medium scale data set in real-time, we first proposed a new kind of volume rendering graphic processor based on object-order splatting algorithm in which flexible transfer function configuration and software optimization such as early opacity termination and transparent voxel occlusion can be achieved. At the same time, the processor also integrates an eight-way interleaved memory system and an efficient address calculation module to accelerate the voxel traversal process and maintain high cache hit rate. Multiple parallel rendering pipelines embedded also can achieve local parallelism on board. Second, in order to render large scale data sets, a real-time and general-purpose volume rendering architecture is also presented in this paper. By utilizing graphic processors on PC clusters, large scale data sets can be visualized resulted from the high parallel speedup among graphic processors.
This paper presents a simple method to calibrate the intrinsic parameters of zoom-lens digital cameras. This method combines the classical calibration algorithm using a planar pattern and the Exchangeable Image File Format (EXIF) metadata of image files captured by digital cameras. The EXIF metadata records many information about the camera’s setting such as the focal length of zooming lens. So we can use the focal length from EXIF to know the zoom lens setting. Firstly, a pre-calibration should be done to know the relationship between zoom lens settings and the intrinsic camera parameters. We take some sample lens settings from the minimum focal length to the maximum one by changing the lens zooming positions, and perform the mono focal calibration for each lens setting configuration. Then we get the coefficients of the polynomial function through curve fitting. After that we can get the intrinsic parameters correspond with the zoom lens setting of new image files shoot by this digital camera. Our experiments show the proposed method can provide accurate intrinsic camera parameters for all the lens settings continuously.
An architecture of distributed virtual reality system is brought forward in this paper. It's based on a C/S system model, and employs a centralized-and-distributed data distribution model. This data distribution model can efficiently realize concurrency control, and easily ensure the data consistency. It also employs a four-layered structure based on Message Queue to accomplish the collaboration management. This structure is platform-independent and very flexible for further extending and upgrading. In this paper, we'll introduce the C/S system model and the centralized-and-distributed data distribution model, and then discuss in detail how the four-layered structure based on Message Queue realizes the collaboration management.
Virtual human is widely used in educational, entertainment, and 3D game software. In this paper, the subsumption architecture, which is popular in robotics, is employed to make a two-level control model. With this model, virtual human can realize collision-free navigation in a dynamic environment. As collision avoidance is realized in the 0-level layer, path planning is completed in the 1-level layer. Finally, an experiment was done in our human animation platform. And the result shows that this control model can guide digital actor navigate collision-freely in the environment with dynamic and static obstacles.
Public perception of flight safety is generally based on the absolute number of accidents and not accident rates. Therefore reduction of the accident rate such that the actual number of accidents decreases must be a primary goal; otherwise the predicted costs and loss of life are not likely to be tolerable by the industry or traveling public. This paper briefs efforts in the virtual flight vision system program to address training pilots avoiding these accidents. The improvement in situational awareness and reduction in pilot workload resulting from the synthetic vision display should allow aircrews to avoid landing short, flying too close to terrain, or blundering onto an active runway. The systems can also aid aircrews in re-planning en route and in the crucial final approach segment, by providing intuitive guidance cues to reduce pilot workload and improve performance.
In this paper we describe an approach to the procedural techniques of pattern generation to be used in rendering, based on genetic algorithms. Procedural textures exhibit many advantages over traditional surface texturing techniques, but unfortunately it is difficult for us to find the correct procedural texture and appropriate parameters to create the desired texture can be a daunting task for even the most experienced user. Upon analysis of genetic programming techniques and image matching evaluation scheme, we attempt to generate procedural 3D cloud texture automatically.
In this paper, Distributed Virtual Reality (DVR) technology applied in Electronical Commerce (EC) is discussed. DVR has the capability of providing a new means for human being to recognize, analyze and resolve the large scale, complex problems, which makes it develop quickly in EC fields. The technology of CSCW (Computer Supported Cooperative Work) and middleware is introduced into the development of EC-DVR system to meet the need of a platform which can provide the necessary cooperation and communication services to avoid developing the basic module repeatedly. Finally, the paper gives a platform structure of EC-DVR system.
This paper discusses the application approach of image analogies in simulating for Chinese painting, presents a simple and effective model. Our algorithm includes analyzing, learning, matching and impression generating. Experimental results demonstrate our approach is efficient for simulating of Chinese painting.
Splatting is a one of the most important object-order volume rendering algorithm. In this paper, a new run length encoding (RLE) accelerated, pre-classification and pre-shade volume splatting algorithm is presented, which enhances the speed of splatting without trading off image quality. This new technique saves rendering time by employing RLE mechanism so that only voxels of interest are processed in splatting. Data structures are defined to fully exploit spatial coherence of volume, including a slice scanline pointer array, a data pointer array, a scanline RLE array and an array storing all data of the non-transparent voxels. And a much fast and accurate sheet buffer splatting method is used in the rendering process, which accelerates the splatting by traversing both the voxel scanline and the image scanline in sheet buffer simultaneously. Experiments practice proves that RLE can efficiently skip over transparent voxels and high speedup can be obtained by using the proposed algorithm. Analysis on speed and memory cost of the algorithm is also conducted. This algorithm may be particularly used in situation where transfer function seldom changes.
Three-dimensional medical reconstruction has been a powerful technique in medical diagnosis, especially by using volume visualization of medical datasets such as those obtained from computed tomography (CT), magnetic resonance imaging (MRI) in recent years. A new medical volume reconstruction algorithm is presented in this paper. By examining the relations among three eigenvalues of local block based moment (LBBM) inertia matrix, the method defines transfer function in the domain of these eigenvalues. The eigenvalues and eigenvectors of the LBBM inertia matrix form a local coordinate system, which measures the local features such as flat, round, and elongated shapes of the object. The optimal window size of local voxel block is determined by experiments, and then two popular volume visualization algorithms are implemented to test the proposed transfer function design method. The proposed method can efficiently depict trivial features in medical datasets, especially useful in the rendering of structures with obvious shapes, such as round, flat, and elongated shapes. The new algorithm can not only result informative rendering results to the doctors, but also can efficiently reduce the time previously spent in trial-and-error process.
Three-dimensional volume reconstruction has gained great popularity as a powerful technique for the visualization of volume datasets such as those obtained from X-ray, computed tomography, and magnetic resonance imaging in recent years. Local features play important part in the classification process for a variety of medical image analysis, computer-aided diagnosis, and three-dimensional reconstruction and visualization applications. By using high-order local statistic features detected by local block based moments, such as flat, round, elongated shapes, together with the local spectral histogram of textures, to act as classification criteria, a three-dimensional medical reconstruction method is proposed in this paper. A volume splatting algorithm by using the proposed classification method is implemented and relatively high-quality rendering results can be obtained when the proposed method is applied in medical reconstructions.