• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권7호
• /
• pp.2585-2598
• /
• 2015

Hand posture recognition has played a very important role in Human Computer Interaction (HCI) and Computer Vision (CV) for many years. The challenge arises mainly due to self-occlusions caused by the limited view of the camera. In this paper, a robust hand posture recognition approach based on 3D point cloud from two RGB-D sensors (Kinect) is proposed to make maximum use of 3D information from depth map. Through noise reduction and registering two point sets obtained satisfactory from two views as we designed, a multi-viewed hand posture point cloud with most 3D information can be acquired. Moreover, we utilize the accurate reconstruction and classify each point cloud by directly matching the normalized point set with the templates of different classes from dataset, which can reduce the training time and calculation. Experimental results based on posture dataset captured by Kinect sensors (from digit 1 to 10) demonstrate the effectiveness of the proposed method.

• 방송공학회논문지
• /
• 제21권6호
• /
• pp.957-964
• /
• 2016

요즘 들어, 3차원 콘텐츠의 수요는 지속적으로 증가하고 있다. 3차원 콘텐츠의 품질은 해당 장면의 깊이 정보에 큰 영향을 받기 때문에 정확한 깊이 정보를 얻는 것이 매우 중요하다. 카메라와 객체 사이의 깊이 정보는 적외선 센서를 이용한 계산을 통해 직접 얻을 수 있다. 최근 들어, KINECT 카메라와 같이 카메라와 물체 사이의 거리를 적외선이나 광신호를 이용하여 직접 측정하는 Time-of-flight (ToF) 기술을 사용하는 깊이 측정 방법이 널리 사용되고 있다. 이러한 방법은 카메라와 객체 사이의 깊이 정보를 실시간으로 획득할 수 있다는 장점을 갖지만, 획득된 깊이맵에 잡음이 발생하고, 깊이맵의 해상도가 낮다는 단점을 갖는다. 최근 들어, 이런 문제를 해결하기 위해서 양방향 결합 업샘플링 방법 (JBU) 이나 잡음 제거 업샘플링 방법 (NAFDU) 과 같은 필터 기반의 방법이 제안되었다. 그러나 이러한 필터 기반의 업샘플링 방법은 업샘플링된 깊이맵에 색상영상의 질감이 복사되는 문제가 발생한다. 이 논문에서는 이러한 문제점을 해결하기 위해 고차 정규화항을 이용하여 에너지 함수를 만들고, 이를 최적화하여 깊이맵을 업샘플링 한다. 또한, 색상과 깊이맵의 경계 정보를 고려한 경계 가중치항을 추가하여 질감 복사 문제를 해결한다. 실험 결과, 제안하는 깊이맵 업샘플링 방법이 기존의 방법에 비해 깊이 정보의 품질은 유지하면서, 질감 복사 문제를 효과적으로 해결할 수 있음을 확인했다.

• 전자통신동향분석
• /
• 제35권5호
• /
• pp.112-122
• /
• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• 스마트미디어저널
• /
• 제1권3호
• /
• pp.15-21
• /
• 2012

깊이 정보의 획득은 다양한 3차원 콘텐츠 제작을 위해서 필수적이다. 깊이 획득은 깊이 정보를 어떻게 획득하느냐에 따라서 크게 두 가지 방식(능동적, 수동적 깊이 센서 방식)으로 나뉜다. 본 논문에서는 몇 가지 측면에서 깊이 정보를 획득하는 방법을 살펴보고, 이들 방식을 통해 깊이를 획득하는 방법뿐 아니라, 각 방식의 약점을 보완하기 위해 두 가지 접근 방법을 혼합하여 깊이 정보를 획득하는 방법도 제시한다. 또한 3차원 비디오에서 매 화면마다 독립적으로 깊이 정보를 추정하여 생기는 깜빡거림 현상과 시각적 피로도를 줄이기 위해서 시간적 상관도를 고려하여 정합 에너지 함수를 정의하는 방법과 후처리하는 방법도 제시한다.

• International Journal of Internet, Broadcasting and Communication
• /
• 제7권1호
• /
• pp.15-19
• /
• 2015

The depth information of an image is used in a variety of applications including 2D/3D conversion, multi-view extraction, modeling, depth keying, etc. There are various methods to acquire depth information, such as the method to use a stereo camera, the method to use the depth camera of flight time (TOF) method, the method to use 3D modeling software, the method to use 3D scanner and the method to use a structured light just like Microsoft's Kinect. In particular, the depth camera of TOF method measures the distance using infrared light, whereas TOF sensor depends on the sensitivity of optical light of an image sensor (CCD/CMOS). Thus, it is mandatory for the existing image sensors to get an infrared light image by bundling several pixels; these requirements generate a phenomenon to reduce the resolution of an image. This thesis proposed a measure to acquire a high-resolution image through gradual area movement while acquiring a low-resolution image through pixel bundling method. From this measure, one can obtain an effect of acquiring image information in which illumination intensity (lux) and resolution were improved without increasing the performance of an image sensor since the image resolution is not improved as resolving a low-illumination intensity (lux) in accordance with the gradual pixel bundling algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권9호
• /
• pp.3924-3940
• /
• 2020

Dynamic hand gesture recognition(d-HGR) plays an important role in human-computer interaction(HCI) system. With the growth of hand-pose estimation as well as 3D depth sensors, depth, and the hand-skeleton dataset is proposed to bring much research in depth and 3D hand skeleton approaches. However, it is still a challenging problem due to the low resolution, higher complexity, and self-occlusion. In this paper, we propose a hand-shape feature extraction(HSFE) network to produce robust hand-shapes. We build a hand-shape model, and hand-skeleton based on LSTM to exploit the temporal information from hand-shape and motion changes. Fusion between two models brings the best accuracy in dynamic hand gesture (DHG) dataset.

• 센서학회지
• /
• 제13권2호
• /
• pp.144-151
• /
• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.

• Transactions on Electrical and Electronic Materials
• /
• 제18권6호
• /
• pp.341-344
• /
• 2017

Infrared (IR) filters were developed to implement integrated three-dimensional (3D) image sensors that are capable of obtaining both color image and depth information at the same time. The combination of light filters applicable to the 3D image sensor is composed of a modified IR cut filter mounted on the objective lens module and on-chip filters such as IR pass filters and color filters. The IR cut filters were fabricated by inorganic $SiO_2/TiO_2$ multilayered thin-film deposition using RF magnetron sputtering. On-chip IR pass filters were synthetized by dissolving various pigments and dyes in organic solvents and by subsequent patterning with photolithography. The fabrication process of the filters is fairly compatible with the complementary metal oxide semiconductor (CMOS) process. Thus, the IR cut filter and IR pass filter combined with conventional color filters are considered successfully applicable to 3D image sensors.

• ETRI Journal
• /
• 제38권5호
• /
• pp.996-1007
• /
• 2016

This paper presents new hole-filling methods for generating multiview images by using depth image based rendering (DIBR). Holes appear in a depth image captured from 3D sensors and in the multiview images rendered by DIBR. The holes are often found around the background regions of the images because the background is prone to occlusions by the foreground objects. Background-oriented priority and gradient-oriented priority are also introduced to find the order of hole-filling after the DIBR process. In addition, to obtain a sample to fill the hole region, we propose the fusing of depth and color information to obtain a weighted sum of two patches for the depth (or rendered depth) images and a new distance measure to find the best-matched patch for the rendered color images. The conventional method produces jagged edges and a blurry phenomenon in the final results, whereas the proposed method can minimize them, which is quite important for high fidelity in stereo imaging. The experimental results show that, by reducing these errors, the proposed methods can significantly improve the hole-filling quality in the multiview images generated.

• 한국정보통신학회논문지
• /
• 제23권6호
• /
• pp.733-739
• /
• 2019

수위측정은 스마트 공장(Smart Factory), 스마트 농장(Smart Farm), 스마트 양식장(Smart Fish Farm) 등 IoT 모니터링 분야에서 활용도가 높다. 그러나 기존의 수위측정 방식은 복잡한 알고리즘과 고가의 센서 위주로 상품성과 산업현장 적용성이 떨어진다. 본 논문에서는 이러한 문제를 해결하고자 비접촉식 스마트센서인 적외선 거리 센서와 홀센서 기반 수위측정 방법을 각각 제안하였다. 센서의 고감도로 인해 발생하는 데이터 오류는 간단한 구조도입을 통해 해결함으로써 범용성을 높였다. 구현된 수위측정 방법은 성능평가 실험을 통해 그 유효성이 검증되었다. 본 연구를 통해 개발된 센서는 IoT 기술 기반 범용성 수위측정 모니터링 시스템으로 확장될 수 있을 것으로 기대한다.