다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.

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A taxonomy and evaluation of dense two-frame stereo correspondence algorithms

Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

/pdf/computer-vision-algorithms-and-applications-25dn6wu83j.pdf

Computer Vision: Algorithms and Applications

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

A hand pattern switch device recognizes a hand pattern from an image of a hand in an image pickup zone and detects a hand motion. One of controlled objects is selected based on the recognized hand pattern and/or hand motion. In accordance with the selected object, a mode of detection of operation information based on hand motion is changed. In a moved distance detecting mode, a moved distance of the hand in the zone is detected as operation information, and in a stop time detecting mode, a stop time of the hand at a stop position to which the hand has been moved in the zone is detected as operation information. The image pickup zone is at a location which is located laterally to a steering wheel and to which a driver can extend his/her arm without changing a driving posture.

Hand pattern switch device

This paper proposes a new scheme for multi-image projective reconstruction based on a projective grid space. The projective grid space is defined by two basis views and the fundamental matrix relating these views. Given fundamental matrices relating other views to each of the two basis views, this projective grid space can be related to any view. In the projective grid space as a general space that is related to all images, a projective shape can be reconstructed from all the images of weakly calibrated cameras. The projective reconstruction is one way to reduce the effort of the calibration because it does not need Euclid metric information, but rather only correspondences of several points between the images. For demonstrating the effectiveness of the proposed projective grid definition, we modify the voxel coloring algorithm for the projective voxel scheme. The quality of the virtual view images re-synthesized from the projective shape demonstrates the effectiveness of our proposed scheme for projective reconstruction from a large number of images.

Shape reconstruction in projective grid space from large number of images

Layered Depth Video (LDV) is recognized as a promising 3D video data representation for supporting advanced 3D video services required in Multiview Video (MVV) systems such as Three-Dimensional Television (3DTV). This representation consists of one full or central view in the form of a video-plus-depth sequence as the main layer, and additional enhancement layers including residual texture and depth data that represent side views. LDV is thus both a derivative of and an alternative to Multiview Video-plus-Depth (MVD) representation by only transmit one full view with associated residual data over the channel. There is a risk, however, of residual data information rapidly increasing as the distance between the center view and side views increases. This occurs when parts of the central view are not visible in the side views, leaving blank spots called disocclusions. These disocclusions may grow larger, which increases the amount of residual data that needs to be sent with the main layer. In this paper, we address the residual layer generation problem. We propose an inpainting-based LDV generation method to reduce the amount of residual data to send by retrieving the missing pixels from the main layer. In the proposed method, we take into account the depth information by distinguishing between foreground and background parts of the scene, at low complexity, during the texture and structure propagation stage of the inpainting process. Experimental results demonstrated the effectiveness of the proposed method.

A Novel Inpainting-Based Layered Depth Video for 3DTV

In this paper, we review diminished reality (DR) studies that visually remove, hide, and see through real objects from the real world. We systematically analyze and classify publications and present a technology map as a reference for future research. We also discuss future directions, including multimodal diminished reality. We believe that this paper will be useful mainly for students who are interested in DR, beginning DR researchers, and teachers who introduce DR in their classes.

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A survey of diminished reality: Techniques for visually concealing, eliminating, and seeing through real objects

/pdf/the-3d-room-digitizing-time-varying-3d-events-by-33y8wu5efw.pdf

Hideo Saito

Papers

Hand pattern switch device

Shape reconstruction in projective grid space from large number of images

A Novel Inpainting-Based Layered Depth Video for 3DTV

A survey of diminished reality: Techniques for visually concealing, eliminating, and seeing through real objects

The 3D Room: Digitizing Time-Varying 3D Events by Synchronized Multiple Video Streams