• Title/Summary/Keyword: 360 image

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Camera Control based on Wireless Mobile and Web Environment (무선 모바일과 웹 환경 기반의 카메라 제어)

  • Seo, Jung-Hee;Park, Hung-Bog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.677-680
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    • 2008
  • Miniaturization of equipments which have wireless network function and sensor have changed utilization method of computer in daily life, and have contributed to development for ubiquitous computing environment. In this paper, we design camera control system based wireless mobile and web-environmental through which nurse, doctor and family of patient can share and observe the information on condition of patient in hospital. Besides, this camera control system makes it possible to integrate diverse equipments of hospital into one system, and to conduct remote control function which can be applied to the patient control system. It is impossible to control shooting direction of camera apparatus in a remote area for observing patient in a hospital room through general web camera. So in this paper, we showed new design; we attached step motor which can rotate 360 degrees to web camera, and the step motor can operate through control board. Besides, we developed application for two environments, mobile and web-based environment, which enables us to offer proper efficiency in accordance with condition of observer through observation of control and collected image data.

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A Deep Neural Network Architecture for Real-Time Semantic Segmentation on Embedded Board (임베디드 보드에서 실시간 의미론적 분할을 위한 심층 신경망 구조)

  • Lee, Junyeop;Lee, Youngwan
    • Journal of KIISE
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    • v.45 no.1
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    • pp.94-98
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    • 2018
  • We propose Wide Inception ResNet (WIR Net) an optimized neural network architecture as a real-time semantic segmentation method for autonomous driving. The neural network architecture consists of an encoder that extracts features by applying a residual connection and inception module, and a decoder that increases the resolution by using transposed convolution and a low layer feature map. We also improved the performance by applying an ELU activation function and optimized the neural network by reducing the number of layers and increasing the number of filters. The performance evaluations used an NVIDIA Geforce GTX 1080 and TX1 boards to assess the class and category IoU for cityscapes data in the driving environment. The experimental results show that the accuracy of class IoU 53.4, category IoU 81.8 and the execution speed of $640{\times}360$, $720{\times}480$ resolution image processing 17.8fps and 13.0fps on TX1 board.

Timeline Synchronization of Multiple Videos Based on Waveform (소리 파형을 이용한 다수 동영상간 시간축 동기화 기법)

  • Kim, Shin;Yoon, Kyoungro
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.197-205
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    • 2018
  • Panoramic image is one of the technologies that are commonly used today. However, technical difficulties still exist in panoramic video production. Without a special camera such as a 360-degree camera, making panoramic video becomes more difficult. In order to make a panoramic video, it is necessary to synchronize the timeline of multiple videos shot at multiple locations. However, the timeline synchronization method using the internal clock of the camera may cause an error due to the difference of the internal hardware. In order to solve this problem, timeline synchronization between multiple videos using visual information or auditory information has been studied. However, there is a problem in accuracy and processing time when using video information, and there is a problem in that, when using audio information, there is no synchronization when there is sensitivity to noise or there is no melody. Therefore, in this paper, we propose a timeline synchronization method between multiple video using audio waveform. It shows higher synchronization accuracy and temporal efficiency than the video information based time synchronization method.

Study of Prediction Model Improvement for Apple Soluble Solids Content Using a Ground-based Hyperspectral Scanner (지상용 초분광 스캐너를 활용한 사과의 당도예측 모델의 성능향상을 위한 연구)

  • Song, Ahram;Jeon, Woohyun;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.559-570
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    • 2017
  • A partial least squares regression (PLSR) model was developed to map the internal soluble solids content (SSC) of apples using a ground-based hyperspectral scanner that could simultaneously acquire outdoor data and capture images of large quantities of apples. We evaluated the applicability of various preprocessing techniques to construct an optimal prediction model and calculated the optimal band through a variable importance in projection (VIP)score. From the 515 bands of hyperspectral images extracted at wavelengths of 360-1019 nm, 70 reflectance spectra of apples were extracted, and the SSC ($^{\circ}Brix$) was measured using a digital photometer. The optimal prediction model wasselected considering the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP) and coefficient of determination of prediction $r_p^2$. As a result, multiplicative scatter correction (MSC)-based preprocessing methods were better than others. For example, when a combination of MSC and standard normal variate (SNV) was used, RMSECV and RMSEP were the lowest at 0.8551 and 0.8561 and $r_c^2$ and $r_p^2$ were the highest at 0.8533 and 0.6546; wavelength ranges of 360-380, 546-690, 760, 915, 931-939, 942, 953, 971, 978, 981, 988, and 992-1019 nm were most influential for SSC determination. The PLSR model with the spectral value of the corresponding region confirmed that the RMSEP decreased to 0.6841 and $r_p^2$ increased to 0.7795 as compared to the values of the entire wavelength band. In this study, we confirmed the feasibility of using a hyperspectral scanner image obtained from outdoors for the SSC measurement of apples. These results indicate that the application of field data and sensors could possibly expand in the future.

The new explore of the animated content using OculusVR - Focusing on the VR platform and killer content - (오큘러스 VR (Oculus VR)를 이용한 애니메이션 콘텐츠의 새로운 모색 - VR 플랫폼과 킬러콘텐츠를 중심으로 -)

  • Lee, Jong-Han
    • Cartoon and Animation Studies
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    • s.45
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    • pp.197-214
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    • 2016
  • Augmented Reality, virtual reality in recently attracted attention throughout the world. and Mix them mixed reality etc., it has had a significant impact on the overall pop culture beyond the scope of science and technology. The world's leading IT company : Google, Apple, Samsung, Microsoft, Sony, LG is focusing on development of AR, VR technology for the public. The many large and small companies developed VR hardware, VR software, VR content. It does not look that makes a human a human operation in the cognitive experience of certain places or situations or invisible through Specific platforms or program is Encompass a common technique that a realization of the virtual space. In particular, out of the three-dimensional image reveals the limitations of the conventional two-dimensional structure - 180, 360 degree images provided by the subjective and objective symptoms such as vision and sense of time and got participants to select it. VR technology that can significantly induce the commitment and participation is Industry as well as to the general public which leads to the attention of colostrum. It was introduced more than 10 related VR works Year 2015 Sundance Film Festival New Frontier program. The appearance VR content : medical, architecture, shopping, movies, animations. Also, 360 individuals can be produced by the camera / video sharing VR is becoming an interactive tunnel between two possible users. Nevertheless, This confusion of values, moral degeneration and the realization of a virtual space that has been pointed out that the inherent. 4K or HUD, location tracking, motion sensors, processing power, and superior 3D graphics, touch, smell, 4D technology, 3D audio technology - It developed more than ever and possible approaches to reality. Thereafter, This is because the moral degeneration, identity, generational conflict, and escapism concerns. Animation is also seeking costs in this category Reality. Despite the similarities rather it has that image, and may be the reason that the animation is pushed back to the VR content creation. However, it is focused on the game and VR technology and the platform that is entertaining, but also seek new points within the animation staying in the flat Given that eventually consist of visual images is clear that VR sought. Finally, What is the reality created in the virtual space using VR technology could be applied to the animation? So it can be seen that the common interest is research on what methods and means applied.

Omni-directional Vision SLAM using a Motion Estimation Method based on Fisheye Image (어안 이미지 기반의 움직임 추정 기법을 이용한 전방향 영상 SLAM)

  • Choi, Yun Won;Choi, Jeong Won;Dai, Yanyan;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.8
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    • pp.868-874
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    • 2014
  • This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

The Variation of Tagging Contrast-to-Noise Ratio (CNR) of SPAMM Image by Modulation of Tagline Spacing

  • Kang, Won-Suk;Park, Byoung-Wook;Choe, Kyu-Ok;Lee, Sang-Ho;Soonil Hong;Haijo Jung;Kim, Hee-Joung
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.360-362
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    • 2002
  • Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. Tagging contrast of such a tagging images can affect to the accuracy of the estimation of tag intersection in order to analyze the myocardial motion. Tagging contrast can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) experimentally. One healthy volunteer was undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner (Gyroscan Intera, Philips Medical System, Netherland). Horizontally modulated stripe patterns were imposed with a range from 3.6mm to 9.6mm of tagline spacing. Images of the left ventricle (LV) wall were acquired at the mid-ventricle level during cardiac cycle with FEEPI (TR/TE/FA=5.8/2.2/10). Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of short tagline spacing than in case of long tagline spacing. In the same heart phase, CNR was increased corresponding with tag line spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing.

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Completion of Occluded Objects in a Video Sequence using Spatio-Temporal Matching (시공간 정합을 이용한 비디오 시퀀스에서의 가려진 객체의 복원)

  • Heo, Mi-Kyoung;Moon, Jae-Kyoung;Park, Soon-Yong
    • The KIPS Transactions:PartB
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    • v.14B no.5
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    • pp.351-360
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    • 2007
  • Video Completion refers to a computer vision technique which restores damaged images by filling missing pixels with suitable color in a video sequence. We propose a new video completion technique to fill in image holes which are caused by removing an unnecessary object in a video sequence, where two objects cross each other in the presence of camera motion. We remove the closer object from a camera which results in image holes. Then these holes are filled by color information of some others frames. First of all, spatio-temporal volumes of occluding and occluded objects are created according to the centroid of the objects. Secondly, a temporal search technique by voxel matching separates and removes the occluding object. Finally. these holes are filled by using spatial search technique. Seams on the boundary of completed pixels we removed by a simple blending technique. Experimental results using real video sequences show that the proposed technique produces new completed videos.

A Study of Digitalizing Analog Gamma Camera Using Gamma-PF Board (Gamma-PF 보드를 이용한 아날로그 감마카메라의 디지털화 연구)

  • Kim, Hui-Jung;So, Su-Gil;Bong, Jeong-Gyun;Kim, Han-Myeong;Kim, Jang-Hwi;Ju, Gwan-Sik;Lee, Jong-Du
    • Journal of Biomedical Engineering Research
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    • v.19 no.4
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    • pp.351-360
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    • 1998
  • Digital gamma camera has many advantages over analog gamma camera. These include convenient quality control, easy calibration and operation, and possible image quantitation which results in improving diagnostic accuracies. The digital data can also be utilized for telemedicine and picture archiving and communication system. However, many hospitals still operate analog cameras and have difficult situation to replace them with digital cameras. We have studied a feasibility of digitalizing an analog gamma camera into a digital camera using Gamma-PF interface board. The physical characteristics that we have measured are spatial resolution, sensitivity, uniformity, and image contrast. The patient's data obtained for both analog and digital camera showed very similar image quality. The results suggest that it may be feasible to upgrade an analog camera into a digital gamma camera in clinical environments.

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A three-stage deep-learning-based method for crack detection of high-resolution steel box girder image

  • Meng, Shiqiao;Gao, Zhiyuan;Zhou, Ying;He, Bin;Kong, Qingzhao
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.29-39
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    • 2022
  • Crack detection plays an important role in the maintenance and protection of steel box girder of bridges. However, since the cracks only occupy an extremely small region of the high-resolution images captured from actual conditions, the existing methods cannot deal with this kind of image effectively. To solve this problem, this paper proposed a novel three-stage method based on deep learning technology and morphology operations. The training set and test set used in this paper are composed of 360 images (4928 × 3264 pixels) in steel girder box. The first stage of the proposed model converted high-resolution images into sub-images by using patch-based method and located the region of cracks by CBAM ResNet-50 model. The Recall reaches 0.95 on the test set. The second stage of our method uses the Attention U-Net model to get the accurate geometric edges of cracks based on results in the first stage. The IoU of the segmentation model implemented in this stage attains 0.48. In the third stage of the model, we remove the wrong-predicted isolated points in the predicted results through dilate operation and outlier elimination algorithm. The IoU of test set ascends to 0.70 after this stage. Ablation experiments are conducted to optimize the parameters and further promote the accuracy of the proposed method. The result shows that: (1) the best patch size of sub-images is 1024 × 1024. (2) the CBAM ResNet-50 and the Attention U-Net achieved the best results in the first and the second stage, respectively. (3) Pre-training the model of the first two stages can improve the IoU by 2.9%. In general, our method is of great significance for crack detection.