• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.273-282
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• 2005

Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.

• Clinical and Experimental Pediatrics
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• v.52 no.7
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• pp.804-810
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• 2009

Purpose : We investigated whether ictal single-photon emission computed tomography (SPECT) with prolonged injection of technetium-99m (99mTc) ethyl cysteinate dimer during repeated spasms can localize the epileptogenic foci in children with infantile spasms. Methods : Fourteen children with infantile spasms (11 boys, 3 girls; mean age, $2.2{\pm}1.3$ years) were examined. When a cluster of spasms was detected during video electroencephalography (EEG) monitoring, $^{99m}Tc$ ethyl cysteinate dimer was slowly and continuously injected for 2 minutes to determine the presence of ictal SPECT. For 7 children, the ictal and interictal SPECT images were visually analyzed, while for the remaining 7 children, the SPECT images were analyzed using the subtraction ictal SPECT coregistered to magnetic resonance imaging (MRI) (SISCOM) technique. Subsequently, we analyzed the association between the ictal SPECT findings and those of other diagnostic modalities such as EEG, MRI, and positron emission tomography (PET). Results : Increase in cerebral blood flow on ictal SPECT involved the epileptogenic foci in 10 cases6 cases analyzed by visual assessment and 4 analyzed by the SISCOM technique. The ictal SPECT and video-EEG findings showed moderate agreement (Kappa=0.57; 95% confidence interval, 0.18-0.96). Conclusion : Ictal SPECT with prolonged injection of a tracer could provide supplementary information to localize the epileptogenic foci in infantile spasms.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.69-74
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• 2004

By the expanding of infrastructure caused by urbanization, new technologies are required to manage various kinds of facilities. GIS has been appraised as valuable technology for facilities management since the 1990s. Therefore, the long and mid term GIS construction plan has been established by the national government and the local government. Some facilities management systems have been built and developed for suppling user-friendly functions. From this point of view, the information system based on the video sequences is considered a more effective way to improve the defects of conventional GIS using the digital map or the image as the base map. Using the video sequences as a base map, the availability of the system ill be increased because the real world information can be furnished to the users. In this study, through the connection between the GIS data, the digital map and the attribute data, and the video sequences taken from the airship using the video geo-referencing and the object tracking, we developed the facilities management system as a prototype which can effectively manage the road utilities. We also presented potentialities of the suggested system for facility management based on the video sequences.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.117-124
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• 2013

In this paper, we present a new method which efficiently estimates a face direction from a sequences of input video images in real time fashion. For this work, the proposed method performs detecting the facial region and major facial features such as both eyes, nose and mouth by using the Haar-like feature, which is relatively not sensitive against light variation, from the detected facial area. Then, it becomes able to track the feature points from every frame using optical flow in real time fashion, and determine the direction of the face based on the feature points tracked. Further, in order to prevent the erroneously recognizing the false positions of the facial features when if the coordinates of the features are lost during the tracking by using optical flow, the proposed method determines the validity of locations of the facial features using the template matching of detected facial features in real time. Depending on the correlation rate of re-considering the detection of the features by the template matching, the face direction estimation process is divided into detecting the facial features again or tracking features while determining the direction of the face. The template matching initially saves the location information of 4 facial features such as the left and right eye, the end of nose and mouse in facial feature detection phase and reevaluated these information when the similarity measure between the stored information and the traced facial information by optical flow is exceed a certain level of threshold by detecting the new facial features from the input image. The proposed approach automatically combines the phase of detecting facial features and the phase of tracking features reciprocally and enables to estimate face pose stably in a real-time fashion. From the experiment, we can prove that the proposed method efficiently estimates face direction.

• Journal of Chest Surgery
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• v.37 no.2
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• pp.160-165
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• 2004

Successful treatment of multi-loculated pleural effusion or thoracic empyema requires effective drainage and definitive diagnosis of causative organism. The purpose of this study was to assess the efficacy of the video-assisted thoracoscopic surgery in the management of thoracic empyema or multi-loculated pleural effusion after chest tube drainage treatment had failed. Material and Method: Between April 2000 and July 2002, 20 patients with thoracic empyema or multi-loculated pleural effusion that failed to chest tube drainage or other procedures who underwent an operation. All patients were assessed by chest-computed tomogram and underwent video assisted thoracoscopic drainage, debridement, biopsy and irrigation of pleural cavity. Result: In 18 cases (90%), underwent successful video-assisted thoracoscopic surgery. In 2 cases, decortications by mini-thoracotomy were necessary. The ratio of sex was 4 : 1 (16 male: 4 female), mean age was 48.9 years old (range, 17∼72 years), mean duration of postoperative chest tube placement was 8.2 days (range, 4∼22 days), mean postoperative hospital stay was 15.2 days (range, 7∼33 days). Causative disease was tuberculosis, pneumonia, trauma and metastatic breast cancer, There were no major postoperative complications. Symptoms improved in all patients and were discharged with OPD follow up. Conclusion: In an early organizing phase of empyema or multi loculated pleural effusion, video-assisted thoracoscopic drainage and debridement are safe and suitable treatment.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.619-623
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• 2008

A lane detection system is one of the major components of intelligent vehicle systems. Difficulties in lane detection mainly come from not only various weather conditions but also a variety of special environment. This paper describes a simple and stable method for the broken lane tracking in various environments. Probabilistic Hough Transform (PHT) and the Least-square method (LSM) are used to track and correct the lane orientation. For the efficiency of the proposed method, two regions of interest (ROIs) are placed in the lower part of each image, where lane marking areas usually appear with less intervention in our system view. By testing in both a set of static images and video sequences, the experiments showed that the proposed approach yielded robust and reliable results.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.17-22
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• 2009

DaVinci processors are popular media processors for implementing embedded multimedia applications. They support dual core architecture: ARM9 core for video I/O handling as well as system management and peripheral handling, and DSP C64+ core for effective digital signal processing. In this paper, we propose our efforts for optimal implementation of object tracking algorithm in DaVinci-based smart camera which is being designed and implemented by our laboratory. The smart camera in this paper is supposed to support object detection, object tracking, object classification and detection of intrusion into surveillance regions and sending the detection event to remote clients using IP protocol. Object tracking algorithm is computationally expensive since it needs to process several procedures such as foreground mask extraction, foreground mask correction, connected component labeling, blob region calculation, object prediction, and etc. which require large amount of computation times. Thus, if it is not implemented optimally in Davinci-based processors, one cannot expect real-time performance of the smart camera.

• Smart Media Journal
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• v.12 no.7
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• pp.18-26
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• 2023

In this study, we propose a cow behavior recognition system based on YOLOX and OC-SORT. YOLO X detects targets in real-time and provides information on cow location and behavior. The OC-SORT module tracks cows in the video and assigns unique IDs. The quantitative analysis module analyzes the behavior and location information of cows. Experimental results show that our system demonstrates high accuracy and precision in target detection and tracking. The average precision (AP) of YOLOX was 82.2%, the average recall (AR) was 85.5%, the number of parameters was 54.15M, and the computation was 194.16GFLOPs. OC-SORT was able to maintain high-precision real-time target tracking in complex environments and occlusion situations. By analyzing changes in cow movement and frequency of mounting behavior, our system can help more accurately discern the estrus behavior of cows.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.79-86
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• 2024

In this paper, a novel visual tracking method which can utilize the context of object regions is presented. Conventional methods have the inherent problem of treating all candidate regions independently, where the tracker could not successfully discriminate regions with similar appearances. This was due to lack of contextual modeling in a given scene, where all candidate object regions should be taken into consideration when choosing a single region. The goal of the proposed method is to encourage feature exchange between candidate regions to improve the discriminability between similar regions. It improves upon conventional methods that only consider a single region, and is implemented by employing the MLP-Mixer model for enhanced feature exchange between regions. By implementing channel-wise, inter-region interaction operation between candidate features, contextual information of regions can be embedded into the individual feature representations. To evaluate the performance of the proposed tracker, the large-scale LaSOT dataset is used, and the experimental results show a competitive AUC performance of 0.560 while running at a real-time speed of 65 fps.

• The Journal of the Acoustical Society of Korea
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• v.43 no.5
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• pp.529-535
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• 2024

This paper presents our research on automatic audio panning for media content production. Previously, tracking an audio was done manually. With the advent of the immersive audio era, the need for an automatic audio panning system has increased, yet no substantial research has been progressed to date. Therefore, we propose a computer vision-based human tracking and depth feature processing system which processes depth feature through using 2-dimensional coordinates and models 3-dimensional view transformation for automatic audio panning to ensure audiovisual congruence. Also, this system applies stage size estimation model which gets input as an image and extrapolates stage width and depth as meter unit. Since our system estimates stage sizes and directly applies them to view transformation, no additional depth data training is required. To validate the proposed system, we also conducted a pilot test with Unity based sample video. Our team expects that our system will enable automated audio panning, assisting many audio engineers.