• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.11
• /
• pp.48-56
• /
• 1998

In this paper, a moving object detection and face region extraction algorithm which can be used in video monitoring systems is presented. The proposed algorithm is composed of two stages. In the first stage, each frame of an input video sequence is analyzed using three measures which are based on image pixel difference. If the current frame contains moving objects, their skin regions are extracted using color and frame difference information in the second stage. Since the proposed algorithm does not rely on computationally expensive features like optical flow, it is well suited for real-time applications. Experimental results tested on various sequences have shown the robustness of the proposed algorithm.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.351-354
• /
• 2002

DVR(Digital Video Recorder), a recently popular visual monitoring system, is required to support multi camera channel display(upto 16 channels) with various display modes in real-time. For such a multichannel display system, it is well known that tearing artifacts become more serious. Thus, one needs to design a display system for DVR so that it does not show tearing artifacts as much as possible, but keeps real-time display speed. In this paper, we present our efforts in designing and implementing a display system which rarely ever shows tearing artifacts, but without degradation of required real-time display speed, and which displays character information stably without blinking.

• Journal of Korea Multimedia Society
• /
• v.25 no.6
• /
• pp.807-818
• /
• 2022

In order to further improve the accuracy and time efficiency of behavior recognition in intelligent monitoring scenarios, a human behavior recognition algorithm based on YOLO combined with LSTM and CNN is proposed. Using the real-time nature of YOLO target detection, firstly, the specific behavior in the surveillance video is detected in real time, and the depth feature extraction is performed after obtaining the target size, location and other information; Then, remove noise data from irrelevant areas in the image; Finally, combined with LSTM modeling and processing time series, the final behavior discrimination is made for the behavior action sequence in the surveillance video. Experiments in the MSR and KTH datasets show that the average recognition rate of each behavior reaches 98.42% and 96.6%, and the average recognition speed reaches 210ms and 220ms. The method in this paper has a good effect on the intelligence behavior recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2148-2161
• /
• 2019

In this paper, we present a real-time cattle action recognition algorithm to detect the estrus phase of cattle from a live video stream. In order to classify cattle movement, specifically, to detect the mounting action, the most observable sign of the estrus phase, a simple yet effective feature description exploiting motion history images (MHI) is designed. By learning the proposed features using the support vector machine framework, various representative cattle actions, such as mounting, walking, tail wagging, and foot stamping, can be recognized robustly in complex scenes. Thanks to low complexity of the proposed action recognition algorithm, multiple cattle in three enclosures can be monitored simultaneously using a single fisheye camera. Through extensive experiments with real video streams, we confirmed that the proposed algorithm outperforms a conventional human action recognition algorithm by 18% in terms of recognition accuracy even with much smaller dimensional feature description.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.4
• /
• pp.85-94
• /
• 2004

Object tracking in a real time image is one of interesting subjects in computer vision and many Practical application fields during the past couple of years. But sometimes existing systems cannot find all objects by recognizing background noise as object. This paper proposes a method of object detection and tracking using adaptive background image in real time. To detect object which is not influenced by illumination and to remove noise in background image, this system generates adaptive background image by real time background image updating. This system detects object using the difference between background image and input image from camera. After setting up Minimum Bounding Rectangle(MBR) using the internal point of detected object, the system tracks object through this MBR In addition, this paper evaluates the test result about performance of proposed method as compared with existing tracking algorithm.

• Journal of IKEEE
• /
• v.18 no.4
• /
• pp.612-619
• /
• 2014

This paper proposes a real-time multi-camera video surveillance system with automatic resolution control using motion detection. In ordinary times, it acquires 4 channels of QVGA images, and it merges them into single VGA image and transmit it. When motion is detected, it automatically increases the resolution of motion-occurring channel to VGA and decreases those of 3 other channels to QQVGA, and then these images are overlaid and transmitted. Thus, it can magnifies and watches the motion-occurring channel while maintaining transmission bandwidth and monitoring all other channels. When it is synthesized with 0.18 um technology, the maximum operating frequency is 110 MHz, which can theoretically support 4 HD cameras.

• Ocean and Polar Research
• /
• v.31 no.4
• /
• pp.415-422
• /
• 2009

The wave observation system in Korea has been established with an emphasis on pointmeasurement based on in situ instrumentations. However, the system cannot fully investigate the coastal wave-related problems that are significantly localized and intensified with three-dimensional regional geometries. Observation technique that can cover local processes with large time and spatial variation needs to be established. Video imaging techniques that can provide continuous monitoring of coastal waves and related phenomena with high spatial and temporal resolutions at minimum cost of instrumentation risks are reviewed together with present status of implementation in Korea. Practical applications of the video imaging techniques are suggested to tackle with various coastal issues of public concern in Korea including, real-time monitoring of wave runup and overtopping of swells on the east coast of Korea, longshore and rip currents, morphological and bathymetric changes, storm surge and tsunami inundation, and abnormal extreme waves in the west coast of Korea, etc.

• Journal of Digital Contents Society
• /
• v.18 no.6
• /
• pp.1009-1015
• /
• 2017

Recently, video surveillance is becoming more and more common as many camera are installed due to crime, terrorism, traffic and security. And systems that control cameras are becoming increasingly general. Video input from the installed camera is monitored by the multiscreen at the central control center, it is essential to simultaneously monitor multiscreen in real-time to quickly respond to situations or dangers. However, monitoring of multiscreen in a mobile environment such as a smart phone is not applied to hardware specifications or network bandwidth problems. For resolving these problems, in this paper, we propose a system that can monitor multiscreen in real-time in mobile-phone environment. We reconstruct the desired multiscreen through transcoding, it is possible to monitor continuously video streaming of multiple cameras, and to have the advantage of being mobile in mobile-phone environment.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.6
• /
• pp.17-24
• /
• 2017

In recent digital broadcasting, up to 250 channels are multiplexed and transmitted. The channel transmission is made in the form of MPEG-2 Transport Stream (TS) and transmits one channel (Video, Audio). In order to check if many broadcast channels are transmitted normally, in multi-channel multi-view system, ability of real-time monitoring is required. In order to monitor efficient multi-channel, a distributed system in which functions and load are distributed should be implemented. In the past, we used an inefficient system that gave all of the functionality to a piece of hardware, which limited the channel acceptance and required a lot of resources. In this paper, we implemented a distributed multi-view system which can reduce resources and monitor them economically through efficient function and load balancing. It is able to implement efficient system by taking charge of decoding, resizing and encoding function in specific server and viewer function in separate server. Through this system, the system was stabilized, the investment cost was reduced by 19.7%, and the wall monitor area was reduced by 52.6%. Experimental results show that efficient real-time channel monitoring for multi-channel digital broadcasting is possible.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.2
• /
• pp.829-842
• /
• 2018

Unmanned Aerial Vehicle (UAV) is diversely utilized in our lives such as daily hobbies, specialized video image taking and disaster prevention activities. New ways of UAV application have been explored recently such as UAV-based delivery. However, most UAV systems are being utilized in a passive form such as real-time video image monitoring, filmed image ground analysis and storage. For more proactive UAV utilization, there should be higher-performance UAV and large-capacity memory than those presently utilized. Against this backdrop, this study described the general matters on proactive software platform and high-performance UAV hardware for real-time target tracking; implemented research on its design and implementation, and described its implementation method. Moreover, in its established platform, this study measured and analyzed the core-specific CPU consumption.