• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1845_1846
• /
• 2009

본 논문에서는 특징 벡터를 이용한 강인한 물체 추적 방법을 제안한다. 먼저, 초기 이동 물체의 움직임 영역을 추출하고, KLT알고리즘을 입력 영상에 적용시켜 특징 벡터들을 추출한다. 초기 추출된 이동 물체의 움직임 영역에 추출된 특징 벡터를 적용시켜 1차 정규화 한다. 그 후, RGB 칼라모델과 HSI 칼라모델을 이용하여 이동 물체에 대한 Blob 영역을 설정하고 설정된 Blob 영역에 대해 1차 특징벡터를 Snake 알고리즘으로 동정하여 2차 정규화 과정을 마무리 한다. 최종 정규화 된 특징 벡터를 Particle filter에 입력 데이터로 이용하여 이동 물체를 추적 한다. 마지막으로, 복잡한 환경에서 실험을 통해 그 응용 가능성을 증명한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.478-480
• /
• 2001

본 논문에서는 실제 도로 영상에서 움직이는 물체를 검출하고 판별하기 위한 새로운 방법을 제안한다. 제안된 방법은 연속된 영상의 차영상에 적응적 임계간을 적용하여 움직임이 있는 후보 영역을 검출한다. 검출된 후보영역에 관심의 대상이 되는 물체의 포함 여부를 판별하기 위해 신경망을 사용한다. 신경망의 입력으로 사용되는 특징 벡터들의 차원을 줄이기 위해, 후보 영역의 스케일 공간 웨이블릿 특징 벡터 (scale-space wavelet feature vector)들을 사용한다. 제안된 방법은 비디오 기반의 응용 프로그램에 유용하게 이용될 수 있으며 특히, 시간에 따라 조명이 변하거나 잡음이 포함된 비디오 영상에 대해 좋은 결과를 얻을 수 있다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06c
• /
• pp.448-450
• /
• 2012

본 논문에서는 Kinect 방식의 RGB-D 영상센서를 사용하여, 깊이(Depth) 영상으로부터 3차원 객체의 기하정보를 표현하는 표면 정규 벡터(Surface Normal Vector)를 추출하고, 그 결과를 영상화하는 방법을 제안하며, 제안된 방법으로 생성된 영상으로부터 깊이 영상의 특징점 및 특징 기술자를 추출하여 3차원 객체 인식 성능을 향상시키는 방법을 제안한다. 또한 생성된 RGB-D 특징 기술자들을 객체 단위로 구분 가능한 코드북(CodeBook) 학습을 통한 인식방법을 제안하여 객체의 인식 성능을 높이는 방법을 제안한다. 제안하는 RGB-D 기반의 특징 추출 및 학습 방법은 텍스쳐 유무, 카메라 회전 및 이동 변화 등의 환경변화에 강건함을 실험적으로 증명하였으며, 이 방법은 Kinect 방식의 RGB-D 영상을 사용하는 3차원 객체/공간 인식 및 추적, 혹은 이를 응용하는 증강현실 시스템에 적용하여 사용될 수 있다.

• Journal of the Korea Computer Graphics Society
• /
• v.27 no.3
• /
• pp.65-74
• /
• 2021

3D reconstruction means that reconstructing the 3D shape of the object in an image and a video. We proposed a progressive occupancy network architecture that can recover not only the overall shape of the object but also the local details. Unlike the original occupancy network, which uses a feature vector embedding information of the whole image, we extract and utilize the different levels of image features depending on the receptive field size. We also propose a novel network architecture that applies the image features sequentially to the decoder blocks in the decoder and improves the quality of the reconstructed 3D shape progressively. In addition, we design a novel decoder block structure that combines the different levels of image features properly and uses them for updating the input point feature. We trained our progressive occupancy network with ShapeNet. We compare its representation power with two prior methods, including prior occupancy network(ONet) and the recent work(DISN) that used different levels of image features like ours. From the perspective of evaluation metrics, our network shows better performance than ONet for all the metrics, and it achieved a little better or a compatible score with DISN. For visualization results, we found that our method successfully reconstructs the local details that ONet misses. Also, compare with DISN that fails to reconstruct the thin parts or occluded parts of the object, our progressive occupancy network successfully catches the parts. These results validate the usefulness of the proposed network architecture.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.5
• /
• pp.63-71
• /
• 2008

In this paper, we propose a color based hierarchically propagated particle filter that extends the color based particle filter into the articulated upper body tracking. Since color feature is robust to partial occlusion and rotation, the color based particle filter is widely used for object tracking. However, in articulated body tacking, it is not desirable to use the traditional particle filter because the dimension of the state vector usually is high and thus, many samples are required for robust hacking. To overcome this problem, we use a hierarchical tracking method for each body part based on the blown body part. By using a hierarchical tracking method, we can reduce the number of samples for robust tracking in the cluttered environment. Also for human pose recognition, we classify the human pose into eight categories using Support Vector Machine(SVM) according to the angle between upper- arm and fore-arm. Experimental results show that our proposed method is more efficient than the traditional particle filter.

• Journal of Digital Contents Society
• /
• v.11 no.1
• /
• pp.17-24
• /
• 2010

The purpose of this study is to design and implement a kernel for the support vector machine(SVM) to improve the performance of face recognition. Local feature analysis(LFA) has been well known for its good performance. SVM kernel plays a limited role of mapping low dimensional face features to high dimensional feature space but the proposed kernel using LFA is designed for face recognition purpose. Because of the novel method that local face information is extracted from training set and combined into the kernel, this method is expected to apply to various object recognition/detection tasks. The experimental results shows its improved performance.

• 전자공학회논문지 IE
• /
• v.44 no.4
• /
• pp.48-54
• /
• 2007

Due to the diverse utilization of multimedia, interests are increasing towards processing (saving, editing, searching, etc) three dimensional object data. This paper proposes and realizes a retrieval system for three dimensional objects using reflective symmetry. For the retrieval method, a reflective symmetric axis with a projector is used. The symmetric plane is calculated by the reflection symmetry, and the depth buffer is calculated for the symmetric plane. Then, by applying the Fourier Transform to the depth buffer, the feature vector for the object is generated and retrieved. For the sample of inquiry, the model of similar symmetry was extracted using the benchmark data from Konstantz University. Considering that most of the objects have symmetrical characteristics, the proposed method of retrieving three dimensional objects using a reflective symmetric surface is an outstanding retrieval system.

• The KIPS Transactions:PartD
• /
• v.13D no.4 s.107
• /
• pp.455-462
• /
• 2006

Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.56-68
• /
• 2022

In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

• Journal of Korea Multimedia Society
• /
• v.15 no.4
• /
• pp.425-438
• /
• 2012

In this paper, We propose Augmented Reality (AR) System for the interaction between user's hand motion and virtual object motion based on computer vision. The previous AR system provides inconvenience to user because the users have to control the marker and the sensor like a tracker. We solved the problem through hand motion and provide the convenience to the user. Also the motion of virtual object using a physical phenomenon gives a reality. The proposed system obtains geometrical information by the marker and hand. The system environments like virtual space of moving virtual ball and bricks are made by using the geometrical information and user's hand motion is obtained from the hand's information with extracted feature point through the taping hand. And it registers a virtual plane stably by getting movement of the feature points. The movement of the virtual ball basically is parabolic motion with a parabolic equation. When the collision occurs either the planes or the bricks, we show movement of the virtual ball with ball position and normal vector of plane and the ball position is faulted. So we showed corrected ball position through experiment. and we proved that this system can replaced the marker system to compare to jitter of augmented virtual object and progress speed with it.