• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.60-66
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• 2012

In this paper, we propose abandoned object detection algorithm. When abandoned object was occluded other object, the existing methods cannot detect abandoned object because those methods are not able to estimate the location of abandoned object. In order to overcome this problem, the proposed algorithm extracts the corners around abandoned object. The detected corners are linked to center of abandoned object called by supporters. We can then estimate the location of abandoned object by using supporters. Therefore, the proposed algorithm can detect and estimate the location of abandoned object, when abandoned object is occluded by other object. For this reason, the proposed algorithm can be applied to intelligent surveillance system to prevent bomb terror, which disguises as luggage or box.

• Journal of IKEEE
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• v.22 no.4
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• pp.1131-1139
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• 2018

This paper proposes a method of recognition abandoned objects using convolutional neural networks. The method first detects an area for an abandoned object in image and, if there is a detected area, applies convolutional neural networks to that area to recognize which object is represented. Experiments were conducted through an application system that detects illegal trash dumping. The experiments result showed the area of abandoned object was detected efficiently. The detected areas enter the input of convolutional neural networks and are classified into whether it is a trash or not. To do this, I trained convolutional neural networks with my own trash dataset and open database. As a training result, I achieved high accuracy for the test set not included in the training set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.771-788
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• 2020

Detection of abandoned objects for smart video surveillance should be robust and accurate in various situations with low computational costs. This paper presents a new algorithm for abandoned object detection based on the dual background model. Through the template registration of a candidate stationary object and presence authentication methods presented in this paper, we can handle some complex cases such as occlusions, illumination changes, long-term abandonment, and owner's re-attendance as well as general detection of abandoned objects. The proposed algorithm also analyzes video frames at specific intervals rather than consecutive video frames to reduce the computational overhead. For performance evaluation, we experimented with the algorithm using the well-known PETS2006, ABODA datasets, and our video dataset in a live streaming environment, which shows that the proposed algorithm works well in various situations.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.462-470
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• 2011

We proposed a realtime object tracking system that detects the abandoned or disappeared objects. Because these events are caused by human, we used the tracking based algorithm. After the background subtraction by Gaussian mixture model, the shadow removal is applied for accurate object detection. The static object is classified as either of abandoned objects or disappeared object. We assigned monitoring time to the static object to overcome a situation that it is being overlapped by other object. We obtained more accurate detection by using region growing method. We implemented our algorithm by DSP processor and obtained an excellent result throughout the experiment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.69-74
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• 2009

Abandoned objects should be treated as possibly dangerous things for public areas until they turn out to be safe because explosive material or chemical substance is intentionally contained in them for public terrors. For large public areas such as airports or train stations, there are limits in man-power for security staffs to check all the monitors for covering the entire area under surveillance. This is the basic motivation of developing the automatic detection system for dangerous abandoned objects based on vision technology. In this research, well-known DBE is applied to stably extract background images and the HOG algorithm is adapted to discriminate between human and stuff for object classification. To show the effectiveness of the proposed system, experiments are carried out in detecting intrusion for a forbidden area and alarming for abandoned objects in a room under surveillance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.23-29
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• 2010

Nowadays it is required to design intelligent visual surveillance systems which automatically detect abandoned objects in public places to strengthen the social safety. Already recognized abandoned objects can be occluded partially or fully by surrounding people in public places after the first recognition. To improve an essential recognition performance index PAT, the system should overcome the occlusion problems. In this research, a design scheme is newly proposed to construct the robust detection system which is comprised of multiple stages considering the occlusion problem. To show the feasibilities of the proposed system, the evaluation was tried for the prepared image streams including 6 various situations and the experimental results show 96% and 75% in PAT performance for intrusion and abandoning events, respectively. Finally in spite of full occlusions by multiple persons, the proposed system shows the capability to continuously recognize the abandoned object after complex occlusions disappear.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.24-32
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• 2010

In this paper we proposed an object tracking system that detects the abandoned and removed objects, which is to be used in the intelligent surveillance applications. After the GMM based background subtraction and by using histogram method, the static region is identified to detect abandoned and removed objects. Since the system is implemented on DSP chip, it operates in realtime and is programmable. The input videos used in the experiment contain various indoor and outdoor scenes, and they are categorized into three different complexities; low, midium and high. By 10 times of experiment, we obtained high detection ratio at low and medium complexity sequences. On the high complexity video, successful detection ratio was relatively low because the scene contains crowdedness and repeated occlusion. In the future work, these complicated situation should be solved.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.253-255
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• 2004

The mining-related damages such as ground subsidence, acid mine drainage(AMD), and deforestation in the abandoned underground coal mine areas become an object of public concern. Therefore, the system to manage the miningrelated damages is needed for the effective drive of rehabilitation activities. The management system for Abandoned Underground Coal Mine using GIS includes the database about mining record and information associated with the mining-related damages and application programs to support mine damage prevention business. Also, this system would support decision-making policy for rehabilitation and provide basic geological data for regional construction works in abandoned underground coal mine areas.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.39-45
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• 2020

Recently the terrors have been attempted in the public places of the nations such as United states, England and Japan by explosive things, toxic materials and so on. It is understood that the method in which dangerous objects are put in public places is one of the difficult types in detection. While there are the cameras recording videos for many spots in public places, it is very hard for the security personnel to monitor every videos. Nowadays the smart softwares which can analyzing videos automatically are utilized to detect abandoned objects. The method by Lin et al. shows comparatively high detection rates for abandoned objects but it is not easy to obtain the shape information because there is a tendency that the number of the pixels decreases abruptly along the time goes due to the characteristics of short-term background images. In this research a novel method is proposed to successfully extract the shape of the abandoned object by analysing the characteristics of area variation. The experiment results show that the proposed method has better performance in extracting shape information in comparison with the precedent approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.25-30
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• 2012

It is important to detect dangerous objects which are intentionally abandoned in public places. Nowadays visual surveillance system is required to enhance the performance in two ways : high resolution and wireless linking ability. In this study the design of visual surveillance system is newly proposed to detect abandoned objects for social security purpose based on wireless high resolution image transmission technology. Also, to enhance PED, PAT performance, the tracking algorithm is included in the previous visual surveillance software scheme. By implementing proposed design scheme on the real wireless high resolution image transmission system, the effectiveness of the overall system is shown with the transmission performance of 4.0 Gbps speed.