• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.83-94
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• 2021

The need for recognition of partially occluded objects is increasing in the area of computer vision applications. Occlusion causes significant problems in identifying and locating an object. In this paper, an annealed Hopfield network (AHN) is proposed for detecting threat objects in passengers' check-in baggage. AHN is a deterministic approximation that is based on the hybrid Hopfield network (HHN) and annealing theory. AHN uses boundary features composed of boundary points and corner points which are extracted from input images of threat objects. The critical temperature also is examined to reduce the run time of AHN. Extensive computational experiments have been conducted to compare the performance of the AHNwith that of the HHN.

• Convergence Security Journal
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• v.24 no.1
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• pp.77-82
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• 2024

Recent research has seen significant improvements in various object detection and classification models overall. However, the study of object detection and classification in situations where objects are partially obscured remains an intriguing research topic. Particularly in the military domain, unmanned combat systems are often used to detect and classify objects, which are typically partially concealed or camouflaged in military scenarios. In this study, a method is proposed to enhance the classification performance of partially obscured objects. This method involves adding occlusions to specific parts of object images, considering the surrounding environment, and has been shown to improve the classification performance for concealed and obscured objects. Experimental results demonstrate that the proposed method leads to enhanced object classification compared to conventional methods for concealed and obscured objects.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.259-260
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• 2009

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.20-28
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• 1989

The recognition of partially occluded objects is of prime importance for industrial machine vision applications and to solve real provlems in factory automation. This paper describes a method tc solve the problem of occlusion in a two dimensional scene. The technique consists of three steps: searching of border, extracting of line segments and clustering of hypotheses by matching probability. Computer simulation results have been tested for 20 scenes contained the 80 models, and have obtained 95% of properly correct recognition rate on the average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.712-717
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• 2013

In this paper, we propose a performance-enhanced object recognition by using nonlinear 3D correlator based on pixel restoration. In the proposed method, elemental images of the 3D target that are partially occluded by a foreground object are picked up and transformed into sub-images. By using the block-matching algorithm, the occluded target regions of each sub-image are estimated and removed. After that, the missing pixels in each sub-image are reestablished by using the pixel-restoration method. Finally, through the nonlinear cross-correlations between the reconstructed reference and the target plane images, the improved object recognition can be performed. To show the feasibility of the proposed method, some preliminary experiments are carried out and results are presented by comparing the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.128-134
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• 2012

In this paper, we propose a novel approach to enhance the recognition performance of a far and partially occluded three-dimensional (3-D) target in computational curving-effective integral imaging (CEII) by using the direct pixel-mapping (DPM) method. With this scheme, the elemental image array (EIA) originally picked up from a far and partially occluded 3-D target can be converted into a new EIA just like the one virtually picked up from a target located close to the lenslet array. Due to this characteristic of DPM, resolution and quality of the reconstructed target image can be highly enhanced, which results in a significant improvement of recognition performance of a far 3-D object. Experimental results reveal that image quality of the reconstructed target image and object recognition performance of the proposed system have been improved by 1.75 dB and 4.56% on the average in PSNR (peak-to-peak signal-to-noise ratio) and NCC (normalized correlation coefficient), respectively, compared to the conventional system.

• Journal of KIISE:Software and Applications
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• v.33 no.9
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• pp.741-750
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• 2006

In this paper, we propose a method for reconstructing a 3D object (or a set of objects) from a 2D drawing provided by a designer. The input 2D drawing consists of a set of contours that may partially overlap each other or be self-overlapping. Accordingly, the resulting 3D object(s) may occlude each other or be self-occluding. The proposed method is composed of three major steps: 2D contour analysis, 3D skeleton computation, and 3D object construction. Our main contribution is to compute the 3D skeleton from the self-intersecting 2D counterpart. We formulate the 3D skeleton construction problem as a sequence of optimization problems, to shape the skeleton and place it in the 3D space while satisfying C1-continuity and intersection-free conditions. Our method is mainly for a silhouette-based sketching interface for the design of 3D objects including self-intersecting objects.

• 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.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.281-286
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• 2007

비디오 복원(video completion)은 비디오 영상에서 색상값에 대한 정보가 없는 픽셀에 적절한 색을 채워 영상을 복원하는 기술이다. 본 논문에서는 움직이는 두 물체가 교차하는 입력영상으로부터 하나의 물체를 제거함으로 발생하는 홀(hole)을 채우는 비디오 복원 기술을 제안한다. 입력 영상에서의 두 물체 중 카메라와 가까운 물체를 제거함으로써 영상의 홀이 발생하게 되고, 이 홀을 다른 프레임들의 정보를 이용하여 채움으로써 가려진 물체를 복원한다. 모든 프레임에 대해 각 물체의 중심을 추정하여 물체의 중심을 기준으로 시-공간 볼륨(spatio-temporal volume)을 생성하고, 복셀 매칭(voxel matching)을 통한 시간적 탐색을 수행한 후 두 물체를 분리한다. 가리는 물체 영역으로 판단 된 부분을 삭제하고 공간적 탐색 방법을 이용하여 홀을 채워 가려짐이 있는 물체를 복원하는 과정을 소개한다. 실험 결과를 통해 제안한 기술이 비교적 자연스러운 결과를 얻을 수 있다는 것을 보여준다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.682-689
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• 2019

In part-based image representation, the partial shapes of an object are represented as basis vectors, and an image is decomposed as a linear combination of basis vectors where the coefficients of those basis vectors represent the partial (or local) feature of an object. In this paper, a face recognition for occluded faces is proposed in which face images are represented using non-negative matrix factorization(NMF), one of part-based representation techniques, and recognized using an artificial neural network technique. Standard NMF, projected gradient NMF and orthogonal NMF were used in part-based representation of face images, and their performances were compared. Learning vector quantizer were used in the recognizer where Euclidean distance was used as the distance measure. Experimental results show that proposed recognition is more robust than the conventional face recognition for the occluded faces.