• Title/Summary/Keyword: depth camera

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Layered Depth Image Representation And H.264 Encoding of Multi-view video For Free viewpoint TV (자유시점 TV를 위한 다시점 비디오의 계층적 깊이 영상 표현과 H.264 부호화)

  • Shin, Jong Hong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.7 no.2
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    • pp.91-100
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    • 2011
  • Free viewpoint TV can provide multi-angle view point images for viewer needs. In the real world, But all angle view point images can not be captured by camera. Only a few any angle view point images are captured by each camera. Group of the captured images is called multi-view image. Therefore free viewpoint TV wants to production of virtual sub angle view point images form captured any angle view point images. Interpolation methods are known of this problem general solution. To product interpolated view point image of correct angle need to depth image of multi-view image. Unfortunately, multi-view video including depth image is necessary to develop a new compression encoding technique for storage and transmission because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method using layered depth image representation and H.264/AVC video coding technology. In experimental results, confirmed high compression performance and good quality reconstructed image.

Correction Method for Measurement Failure Pixels in Depth Picture using Surface Modeling (표면 모델링을 통한 깊이 영상 내 측정 실패 화소 보정 방법)

  • Lee, DongSeok;Kwon, SoonKak
    • Journal of Korea Society of Industrial Information Systems
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    • v.24 no.5
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    • pp.1-8
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    • 2019
  • In this paper, we propose a correcting method of depth pixels which are failed to measure since temporary camera error. A block is modeled to plane and sphere surfaces through measured depth pixels in the block. Depth values in the block are estimated through each modeled surface and a error for the modeled surface is calculated by comparing the original and estimated pixels, then the surface which has the least error is selected. The pixels which are failed to measure are corrected by estimating depth values through selected surface. Simulation results show that the proposed method increases the correction accuracy by an average of 20% compared with the correction method of $5{\times}5$ median method.

Development of HD Resolution Stereoscopic Camera and Apparatus for Recognizing Depth of Object (HD 해상도 스테레오 영상 카메라 구현과 거리 인식 응용)

  • Han, Byung-Wan;Lim, Sung-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.1
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    • pp.351-357
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    • 2013
  • Two cameras which function like human eyes, are needed to make 3D stereoscopic image. That is, stereoscopic image is made via 3 dimensional image processing for combining two images from left and right camera. In this paper two high resolution zoom cameras are used to make HD resolution stereoscopic camera. And the algorithm which convert to stereoscopic image from HD resolution zoom camera image, is implemented using FPGA for real-time operation. The algorithm which measure the depth of object between left and right image is proposed.

Object detection using a light field camera (라이트 필드 카메라를 사용한 객체 검출)

  • Jeong, Mingu;Kim, Dohun;Park, Sanghyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.109-111
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    • 2021
  • Recently, computer vision research using light field cameras has been actively conducted. Since light field cameras have spatial information, various studies are being conducted in fields such as depth map estimation, super resolution, and 3D object detection. In this paper, we propose a method for detecting objects in blur images through a 7×7 array of images acquired through a light field camera. The blur image, which is weak in the existing camera, is detected through the light field camera. The proposed method uses the SSD algorithm to evaluate the performance using blur images acquired from light field cameras.

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3D Image Processing for Recognition and Size Estimation of the Fruit of Plum(Japanese Apricot) (3D 영상을 활용한 매실 인식 및 크기 추정)

  • Jang, Eun-Chae;Park, Seong-Jin;Park, Woo-Jun;Bae, Yeonghwan;Kim, Hyuck-Joo
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.130-139
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    • 2021
  • In this study, size of the fruit of Japanese apricot (plum) was estimated through a plum recognition and size estimation program using 3D images in order to control the Eurytoma maslovskii that causes the most damage to plum in a timely manner. In 2018, night shooting was carried out using a Kinect 2.0 Camera. For night shooting in 2019, a RealSense Depth Camera D415 was used. Based on the acquired images, a plum recognition and estimation program consisting of four stages of image preprocessing, sizeable plum extraction, RGB and depth image matching and plum size estimation was implemented using MATLAB R2018a. The results obtained by running the program on 10 images produced an average plum recognition error rate of 61.9%, an average plum recognition error rate of 0.5% and an average size measurement error rate of 3.6%. The continued development of these plum recognition and size estimation programs is expected to enable accurate fruit size monitoring in the future and the development of timely control systems for Eurytoma maslovskii.

Computer-generated hologram based on the depth information of active sensor (능동형 센서의 깊이 정보를 이용한 컴퓨터 형성 홀로그램)

  • Kim, Sang-Jin;Kang, Hoon-Jong;Yoo, Ji-Sang;Lee, Seung-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.43 no.10 s.352
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    • pp.22-27
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    • 2006
  • In this paper, we propose a method that can generate a computer-generated hologram (CGH) from the depth stream and color image outputs provided by an active sensor add-on camera. Distinguished from an existing holographic display system that uses a computer graphic model to generate CGH, this method utilizes a real camera image including a depth information for each object captured by the camera, as well as color information. This procedure consists of two steps that the acquirement of a depth-annotated image of real object, and generation of CGH according to the 3D information that is extracted from the depth cue. In addition, we display the generated CGH via a holographic display system. In experimental system we reconstruct an image made from CGH with a reflective LCD panel that had a pixel-pitch of 10.4um and resolution of 1408X1050.

RGB-Depth Camera for Dynamic Measurement of Liquid Sloshing (RGB-Depth 카메라를 활용한 유체 표면의 거동 계측분석)

  • Kim, Junhee;Yoo, Sae-Woung;Min, Kyung-Won
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.32 no.1
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    • pp.29-35
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    • 2019
  • In this paper, a low-cost dynamic measurement system using the RGB-depth camera, Microsoft $Kinect^{(R)}$ v2, is proposed for measuring time-varying free surface motion of liquid dampers used in building vibration mitigation. Various experimental studies are conducted consecutively: performance evaluation and validation of the $Kinect^{(R)}$ v2, real-time monitoring using the $Kinect^{(R)}$ v2 SDK(software development kits), point cloud acquisition of liquid free surface in the 3D space, comparison with the existing video sensing technology. Utilizing the proposed $Kinect^{(R)}$ v2-based measurement system in this study, dynamic behavior of liquid in a laboratory-scaled small tank under a wide frequency range of input excitation is experimentally analyzed.

Unsupervised Monocular Depth Estimation Using Self-Attention for Autonomous Driving (자율주행을 위한 Self-Attention 기반 비지도 단안 카메라 영상 깊이 추정)

  • Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.182-189
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    • 2023
  • Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

Image Synthesis and Multiview Image Generation using Control of Layer-based Depth Image (레이어 기반의 깊이영상 조절을 이용한 영상 합성 및 다시점 영상 생성)

  • Seo, Young-Ho;Yang, Jung-Mo;Kim, Dong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.8
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    • pp.1704-1713
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    • 2011
  • This paper proposes a method to generate multiview images which use a synthesized image consisting of layered objects. The camera system which consists of a depth camera and a RGB camera is used in capturing objects and extracts 3-dimensional information. Considering the position and distance of the synthesizing image, the objects are synthesized into a layered image. The synthesized image is spaned to multiview images by using multiview generation tools. In this paper, we synthesized two images which consist of objects and human and the multiview images which have 37 view points were generated by using the synthesized images.