• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.2
• /
• pp.435-442
• /
• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.741-747
• /
• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.10
• /
• pp.326-331
• /
• 2019

In the real world, there are both dynamic objects and static objects, but an autonomous vehicle or mobile robot cannot distinguish between them, even though a human can distinguish them easily. It is important to distinguish static objects from dynamic objects clearly to perform autonomous driving successfully and stably for an autonomous vehicle or mobile robot. To do this, various sensor systems can be used, like cameras and LiDAR. Stereo camera images are used often for autonomous driving. The stereo camera images can be used in object recognition areas like object segmentation, classification, and tracking, as well as navigation areas like 3D world reconstruction. This study suggests a method to distinguish static/dynamic objects using stereo vision for an online autonomous vehicle and mobile robot. The method was applied to a 3D world map reconstructed from stereo vision for navigation and had 99.81% accuracy.

• Journal of The Korean Association For Science Education
• /
• v.33 no.1
• /
• pp.193-207
• /
• 2013

The purpose of this study was to investigate middle school and science-gifted students' conceptions about motion of objects on the surface of the earth and the moon. The subjects were 61 first-, 51 second-, 51 third-year students, for a total of 163 in a middle school and 32 science-gifted students from a university-affiliated sciencegifted education center for secondary school students. The research contents were conceptions about motion of objects by the vertical direction, an inclined plane and horizontal plane on the surface of the earth and the moon. The questions were as follows: If two balls, same size but different mass, were put on, thrown over, by the vertical direction, an inclined plane and a horizontal plane on the surface of the earth and the moon at the same time and speed, which one would arrive faster than the other?; In the same mass in the earth and the moon, how fast could the object reach to which location, the earth or the moon? The results showed that science-gifted students offer meaningful difference on the concept of objects in motion at the vertical direction, an inclined plane and a horizontal plane on the earth and at the vertical direction on the moon than general middle school students. There were meaningful difference on the vertical up direction, an inclined plane and a horizontal plane in the same situation in the earth and the moon. Finally, based on the results of our study, we discuss possible educational implications for teaching the concept of objects in motion.

• Journal of Plant Biotechnology
• /
• v.30 no.4
• /
• pp.399-403
• /
• 2003

In order to understand the protection effects of antioxidant enzymes against oxidative stress caused by various environmental stresses, transgenic tobacco (Nicotiana tabacum cv, Xanthi) plants expressing both copper/zinc superoxide dismutase (CuZnSOD) and ascorbate peroxidase (APX) in chloroplasts (referred to as CA plants) were subjected to highlight (1,100$\mu$mol m$^{-2}$ sec$^{-1}$) and chilling at 4$^{\circ}C$. The protection effects of CA plants using leaf discs were compared with those of transgenic plants expressing either CuZnSOD or APX in chloroplasts (SOD plants or APX plants, respectively) and non-transgenic (NT) plants. CA plants showed about 15％ protection in the photosynthetic efficiency (Fv/Fm) of photosystem II relative to NT plants 1 hr after treatment of both highlight and chilling, whereas they showed about 23％ protection in the redox state of P700 in photosystem I at 3 hr after treatment. SOD plants or APX plants showed an intermediate protection effect between CA plants and NT plants. These results demonstrated that the coexpression of CuZnSOD and APX in chloroplasts importantly involves in the protection effects against oxidative stress caused by various environmental stresses.

• Journal of Internet Computing and Services
• /
• v.19 no.6
• /
• pp.91-99
• /
• 2018

Sketch-based 3D object retrieval is a convenient way to search for various 3D data using human-drawn sketches as query. In this paper, we propose a new method of using Sketch CNN, Wasserstein CNN and Wasserstein center loss for sketch-based 3D object search. Specifically, Wasserstein center loss is a method of learning the center of each object category and reducing the Wasserstein distance between center and features of the same category. To do this, the proposed 3D object retrieval is performed as follows. Firstly, Wasserstein CNN extracts 2D images taken from various directions of 3D object using CNN, and extracts features of 3D data by computing the Wasserstein barycenters of features of each image. Secondly, the features of the sketch are extracted using a separate Sketch CNN. Finally, we learn the features of the extracted 3D object and the features of the sketch using the proposed Wasserstein center loss. In order to demonstrate the superiority of the proposed method, we evaluated two sets of benchmark data sets, SHREC 13 and SHREC 14, and the proposed method shows better performance in all conventional metrics compared to the state of the art methods.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.6
• /
• pp.897-906
• /
• 2017

Projection Mapping, also known as Spatial Augmented Reality(SAR) has attracted much attention recently and used for many division, which can augment physical objects with projected various virtual replications. However, conventional approaches towards projection mapping have faced some limitations. Target objects' geometric transformation property does not considered, and movements of flexible objects-like paper are hard to handle, such as folding and bending as natural interaction. Also, precise registration and tracking has been a cumbersome process in the past. While there have been many researches on Projection Mapping on static objects, dynamic projection mapping that can keep tracking of a moving flexible target and aligning the projection at interactive level is still a challenge. Therefore, this paper propose a new method using Unity3D and ARToolkit for high-speed robust tracking and dynamic projection mapping onto non-rigid deforming objects rapidly and interactively. The method consists of four stages, forming cubic bezier surface, process of rendering transformation values, multiple marker recognition and tracking, and webcam real time-lapse imaging. Users can fold, curve, bend and twist to make interaction. This method can achieve three high-quality results. First, the system can detect the strong deformation of objects. Second, it reduces the occlusion error which reduces the misalignment between the target object and the projected video. Lastly, the accuracy and the robustness of this method can make result values to be projected exactly onto the target object in real-time with high-speed and precise transformation tracking.

• Proceedings of the KIEE Conference
• /
• 2008.04a
• /
• pp.168-169
• /
• 2008

물체 인식에 사용되는 특징 벡터로 영역과 점이 있다. 우리는 영역 특징을 기반으로 하는 물체 인식 알고리즘과 특징점 정보를 기반으로 하는 물체 인식 알고리즘이 상호 보완될 수 있도록 하는 방범을 소개한다. 우리가 제안한 방법에서는 두 가지 알고리즘의 중간 결과가 상호 보완되게 함으로써, 물체 인식의 성능을 향상시키고자 하였다. 또한 두 가지의 물체 인식 알고리즘을 병렬 처리될 수 있도록 함으로써, 사용자로 하여금 신속하게 인식 결과를 확인할 수 있도록 하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2013.01a
• /
• pp.227-228
• /
• 2013

본 논문에서는 연속적으로 입력되는 스테레오 입체 영상으로부터 2차원과 3차원의 특징을 결합하여 군집화함으로써 대상 물체를 보다 강건하게 분할하는 기법을 제안한다. 제안된 방법에서는 촬영된 장면의 좌우 영상으로부터 스테레오 정합 알고리즘을 이용해 영상의 각 화소별로 카메라와 물체 사이의 거리를 나타내는 깊이 특징을 추출한다. 그런 다음, 깊이와 색상 특징을 효과적으로 군집화하여 배경에 해당하는 영역을 제외하고, 전경에 해당하는 대상 물체를 감지한다. 실험에서는 제안된 방법을 여러가지 영상에 적용하여 테스트를 해 보았으며, 제안된 방법이 기존의 2차원 기반의 물체 분리 방법에 비해 보다 강건하게 대상물체를 분할함을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.1
• /
• pp.37-45
• /
• 2002

This paper proposes new features for recognizing telltale bulb in a cluster. A typical feature employed in model-based pattern recognition is polygonal approximation points of object. But recognition using these dominant points has many mismatching counts in small model such as telltale bulb. To reduce mismatching counts, proposed features are the circle distribution of object pixel and the ratio of distance from center to boundary in object. This Paper also proposes new decision function using three features. In simulation result, we make a comparison mismatching counts between recognition using dominant points and the new recognition algorithm using three features.