• Title/Summary/Keyword: single-view camera

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GPU-Accelerated Single Image Depth Estimation with Color-Filtered Aperture

  • Hsu, Yueh-Teng;Chen, Chun-Chieh;Tseng, Shu-Ming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.1058-1070
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    • 2014
  • There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

Image Analysis Module for AR-based Navigation Information Display (증강현실 기반의 항행정보 가시화를 위한 영상해석 모듈)

  • Lee, Jung-Min;Lee, Kyung-Ho;Kim, Dae-Seok
    • Journal of Ocean Engineering and Technology
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    • v.27 no.3
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    • pp.22-28
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    • 2013
  • This paper suggests a navigation information display system that is based on augmented reality technology. A navigator always has to confirm the information from marine electronic navigation devices and then compare it with the view of targets outside the windows. This "head down" posture causes discomfort and sometimes near accidents such as collisions or missing objects, because he or she cannot keep an eye on the front view of the windows. Augmented reality can display both virtual and real information in a single display. Therefore, we attempted to adapt AR technology to assist navigators. To analyze the outside view of the bridge window, various computer image processing techniques are required because the sea surface has many noises that disturb computer image processing for object detection, such as waves, wakes, light reflection, and so on. In this study, we investigated an analysis module to extract navigational information from images that are captured by a CCTV camera, and we validated our prototype.

Computer Image Processing for AR Conceptional Display 3D Navigational Information (증강현실 개념의 항행정보 가시화를 위한 영상처리 기술)

  • Lee, Jung-Min;Lee, Kyung-Ho;Kim, Dae-Soek;Nam, Byeong-Wook
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2014.10a
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    • pp.245-246
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    • 2014
  • This paper suggests the navigation information display system which is based on augmented reality technology and especially focuses on image analysis technology. Navigator has to always confirm the information from marine electronic navigation devices and then they compare with the view of outside targets of the windows. During this 'head down' posture, they feel uncomfortable and sometimes it cause near-accidents such as collision or missing objects, because he or she cannot keep an eye on the front view of windows. Augmented reality can display both of information of virtual and real in a single display. Therefore we tried to adapt the AR technology to help navigators and have been studied and developed image pre-processing module as a previous research already. To analysis the outside view of the bridge window, we have extracted navigational information from the camera image by using image processing. This paper mainly describes about recognizing ship feature by haar-like feature and filtering region of interest area by AIS data, which are to improve accuracy of the image analysis.

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Performance Simulation of Various Feature-Initialization Algorithms for Forward-Viewing Mono-Camera-Based SLAM (전방 모노카메라 기반 SLAM 을 위한 다양한 특징점 초기화 알고리즘의 성능 시뮬레이션)

  • Lee, Hun;Kim, Chul Hong;Lee, Tae-Jae;Cho, Dong-Il Dan
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.10
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    • pp.833-838
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    • 2016
  • This paper presents a performance evaluation of various feature-initialization algorithms for forward-viewing mono-camera based simultaneous localization and mapping (SLAM), specifically in indoor environments. For mono-camera based SLAM, the position of feature points cannot be known from a single view; therefore, it should be estimated from a feature initialization method using multiple viewpoint measurements. The accuracy of the feature initialization method directly affects the accuracy of the SLAM system. In this study, four different feature initialization algorithms are evaluated in simulations, including linear triangulation; depth parameterized, linear triangulation; weighted nearest point triangulation; and particle filter based depth estimation algorithms. In the simulation, the virtual feature positions are estimated when the virtual robot, containing a virtual forward-viewing mono-camera, moves forward. The results show that the linear triangulation method provides the best results in terms of feature-position estimation accuracy and computational speed.

Fast View Synthesis Using GPGPU (GPGPU를 이용한 고속 영상 합성 기법)

  • Shin, Hong-Chang;Park, Han-Hoon;Park, Jong-Il
    • Journal of Broadcast Engineering
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    • v.13 no.6
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    • pp.859-874
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    • 2008
  • In this paper, we develop a fast view synthesis method that generates multiple intermediate views in real-time for the 3D display system when the camera geometry and depth map of reference views are given in advance. The proposed method achieves faster view synthesis than previous approaches in GPU by processing in parallel the entire computations required for the view synthesis. Specifically, we use $CUDA^{TM}$ (by NVIDIA) to control GPU device. For increasing the processing speed, we adapted all the processes for the view synthesis to single instruction multiple data (SIMD) structure that is a main feature of CUDA, maximized the use of the high-speed memories on GPU device, and optimized the implementation. As a result, we could synthesize 9 intermediate view images with the size of 720 by 480 pixels within 0.128 second.

Learning Spatio-Temporal Topology of a Multiple Cameras Network by Tracking Human Movement (사람의 움직임 추적에 근거한 다중 카메라의 시공간 위상 학습)

  • Nam, Yun-Young;Ryu, Jung-Hun;Choi, Yoo-Joo;Cho, We-Duke
    • Journal of KIISE:Computing Practices and Letters
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    • v.13 no.7
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    • pp.488-498
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    • 2007
  • This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs) in Ubiquitous Smart Space (USS). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

A NEW AUTO-GUIDING SYSTEM FOR CQUEAN

  • CHOI, NAHYUN;PARK, WON-KEE;LEE, HYE-IN;JI, TAE-GEUN;JEON, YISEUL;IM, MYUNGSHI;PAK, SOOJONG
    • Journal of The Korean Astronomical Society
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    • v.48 no.3
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    • pp.177-185
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    • 2015
  • We develop a new auto-guiding system for the Camera for QUasars in the EArly uNiverse (CQUEAN). CQUEAN is an optical CCD camera system attached to the 2.1-m Otto-Struve Telescope (OST) at McDonald Observatory, USA. The new auto-guiding system differs from the original one in the following: instead of the cassegrain focus of the OST, it is attached to the finder scope; it has its own filter system for observation of bright targets; and it is controlled with the CQUEAN Auto-guiding Package, a newly developed auto-guiding program. Finder scope commands a very wide field of view at the expense of poorer light gathering power than that of the OST. Based on the star count data and the limiting magnitude of the system, we estimate there are more than 5.9 observable stars with a single FOV using the new auto-guiding CCD camera. An adapter is made to attach the system to the finder scope. The new auto-guiding system successfully guided the OST to obtain science data with CQUEAN during the test run in 2014 February. The FWHM and ellipticity distributions of stellar profiles on CQUEAN, images guided with the new auto-guiding system, indicate similar guiding capabilities with the original auto-guiding system but with slightly poorer guiding performance at longer exposures, as indicated by the position angle distribution. We conclude that the new auto-guiding system has overall similar guiding performance to the original system. The new auto-guiding system will be used for the second generation CQUEAN, but it can be used for other cassegrain instruments of the OST.

An Improved Motion/Disparity Vector Prediction for Multi-view Video Coding (다시점 비디오 부호화를 위한 개선된 움직임/변이 벡터 예측)

  • Lim, Sung-Chang;Lee, Yung-Lyul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.2
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    • pp.37-48
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    • 2008
  • Generally, a motion vector and a disparity vector represent the motion information of an object in a single-view of camera and the displacement of the same scene between two cameras that located spatially different from each other, respectively. Conventional H.264/AVC does not use the disparity vector in the motion vector prediction because H.264/AVC has been developed for the single-view video. But, multi-view video coding that uses the inter-view prediction structure based on H.264/AVC can make use of the disparity vector instead of the motion vector when the current frame refers to the frame of different view. Therefore, in this paper, we propose an improved motion/disparity vector prediction method that consists of global disparity vector replacement and extended neighboring block prediction. From the experimental results of the proposed method compared with the conventional motion vector prediction of H.264/AVC, we achieved average 1.07% and 1.32% of BD (Bjontegaard delta)-bitrate saving for ${\pm}32$ and ${\pm}64$ of global vector search range, respectively, when the search range of the motion vector prediction is set to ${\pm}16$.

A Fast Vision-based Head Tracking Method for Interactive Stereoscopic Viewing

  • Putpuek, Narongsak;Chotikakamthorn, Nopporn
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1102-1105
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    • 2004
  • In this paper, the problem of a viewer's head tracking in a desktop-based interactive stereoscopic display system is considered. A fast and low-cost approach to the problem is important for such a computing environment. The system under consideration utilizes a shuttle glass for stereoscopic display. The proposed method makes use of an image taken from a single low-cost video camera. By using a simple feature extraction algorithm, the obtained points corresponding to the image of the user-worn shuttle glass are used to estimate the glass center, its local 'yaw' angle, as measured with respect to the glass center, and its global 'yaw' angle as measured with respect to the camera location. With these estimations, the stereoscopic image synthetic program utilizes those values to interactively adjust the two-view stereoscopic image pair as displayed on a computer screen. The adjustment is carried out such that the so-obtained stereoscopic picture, when viewed from a current user position, provides a close-to-real perspective and depth perception. However, because the algorithm and device used are designed for fast computation, the estimation is typically not precise enough to provide a flicker-free interactive viewing. An error concealment method is thus proposed to alleviate the problem. This concealment method should be sufficient for applications that do not require a high degree of visual realism and interaction.

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Analysis method of signal model for synthetic aperture integral imaging (합성 촬영 집적 영상의 신호 모델 해석 방법)

  • Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.11
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    • pp.2563-2568
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    • 2010
  • SAII (synthetic aperture integral imaging) is a useful technique to record many multi view images of 3D objects by using a moving camera and to reconstruct 3D depth images from the recorded multiviews. This is largely composed of two processes. A pickup process provides elemental images of 3D objects and a reconstruction process generates 3D depth images computationally. In this paper, a signal model for SAII is presented. We defined the granular noise and analyzed its characteristics. Our signal model revealed that we could reduce the noise in the reconstructed images and increase the computational speed by reducing the shifting distance of a single camera.