• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1148-1152
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• 2012

In this paper, we propose an intelligent surveillance system using fuzzy contrast and HOG method. This surveillance system is mainly for the intruder detection. In order to enhance the brightness difference, we apply fuzzy contrast and also apply subtraction method to before/after the surveillance. Then the system identifies the intrusion when the difference of histogram between before/after surveillance is sufficiently large. If the incident happens, the camera stops automatically and the analysis of the screen is performed with fuzzy binarization and Blob method. The intruder is detected and tracked in real time by HOG method and linear SVM. The proposed system is implemented and tested in real world environment and showed acceptable performance in both detection rate and tracking success rate.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.235-245
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• 2012

This paper introduce a quiz game contents based on gesture interface. We analyzed the off-line quiz games, extracted its presiding components, and digitalized them so that the proposed game contents is able to substitute for the off-line quiz games. We used the Kinect camera to obtain the depth images and performed the preprocessing including vertical human segmentation, head detection and tracking and hand detection, and gesture recognition for hand-up, hand vertical movement, fist shape, pass and fist-and-attraction. Especially, we defined the interface gestures designed as a metaphor for natural gestures in real world so that users are able to feel abstract concept of movement, selection and confirmation tangibly. Compared to our previous work, we added the card compensation process for completeness, improved the vertical hand movement and the fist shape recognition methods for the example selection and presented an organized test to measure the recognition performance. The implemented quiz application program was tested in real time and showed very satisfactory gesture recognition results.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.164-173
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• 2014

In underwater robotics, vision would be a key element for recognition in underwater environments. However, due to turbidity an underwater optical camera is rarely available. An underwater imaging sonar, as an alternative, delivers low quality sonar images which are not stable and accurate enough to find out natural objects by image processing. For this, artificial landmarks based on the characteristics of ultrasonic waves and their recognition method by a shape matrix transformation were proposed and were proven in Part 1. But, this is not working properly in undulating and dynamically noisy sea-bottom. To solve this, we propose a framework providing a selection phase of likelihood candidates, a selection phase for final candidates, recognition phase and tracking phase in sequence images, where a particle filter based selection mechanism to eliminate fake candidates and a mean shift based tracking algorithm are also proposed. All 4 steps are running in parallel and real-time processing. The proposed framework is flexible to add and to modify internal algorithms. A pool test and sea trial are carried out to prove the performance, and detail analysis of experimental results are done. Information is obtained from tracking phase such as relative distance, bearing will be expected to be used for control and navigation of underwater robots.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.1-8
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• 2005

In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.127-138
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• 2008

Vehicles have recently become one of the main factors affecting our quality of life, and the needs of vehicles are still increasing. As a result, the growth of vehicles generate more crashes every year. One main factor for vehicle crashes is uncareful driving behaviors. Especially, drowsy or fatigue driving behaviors explain about 10-20% of the crashes, and they cause serious results because of the delay of response time and the decrease of object-recognition. Therefore, this research conducted real time image processing tests in order to study how cellular phone usages and drowy(or fatigue) drives affect driving behaviors. A vehicle simulator was used for this research, and the faceLAB 4.5 of Seeing Machines for eye image tracking tests using a small camera was installed in the front of the simulator, and normal and drowsy(or fatigue) driving patterns were analyzed.

• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.55-66
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• 2012

Purpose : During brain MRI scanning, subject's head motion can adversely affect MRI images. To minimize MR image distortion by head movement, we developed an optical tracking system to detect the 3-D movement of subjects. Materials and Methods: The system consisted of 2 CCD cameras, two infrared illuminators, reflective sphere-type markers, and frame grabber with desktop PC. Using calibration which is the procedure to calculate intrinsic/extrinsic parameters of each camera and triangulation, the system was desiged to detect 3-D coordinates of subject's head movement. We evaluated the accuracy of 3-D position of reflective markers on both test board and the real MRI scans. Results: The stereo system computed the 3-D position of markers accurately for the test board and for the subject with glasses with attached optical reflective marker, required to make regular head motion during MRI scanning. This head motion tracking didn't affect the resulting MR images even in the environment varying magnetic gradient and several RF pulses. Conclusion: This system has an advantage to detect subject's head motion in real-time. Using the developed system, MRI operator is able to determine whether he/she should stop or intervene in MRI acquisition to prevent more image distortions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.2
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• pp.159-164
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• 2013

It is well known that a single moving camera video is capable of extracting the 3-dimensional position of an object. With this in mind, current research performed image-based monitoring to establish a floating structure model using a camcorder system. Following this, the present study extracted frame images from digital camcorder video clips and matched the interest points to obtain relative 3D coordinates for both regular and irregular wave conditions. Then, the researchers evaluated the transformation accuracy of the modified SURF-based matching and image-based displacement estimation of the floating structure model in regular wave condition. For the regular wave condition, the wave generator's setting value was 3.0 sec and the cycle of the image-based displacement result was 2.993 sec. Taking into account mechanical error, these values can be considered as very similar. In terms of visual inspection, the researchers observed the shape of a regular wave in the 3-dimensional and 1-dimensional figures through the projection on X Y Z axis. In conclusion, it was possible to calculate the displacement of a floating structure module in near real-time using an average digital camcorder with 30fps video.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.53-62
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• 2011

In this paper, high-tech IT Convergence, to the development of complex technology, special technology, video object recognition technology was considered only as a smart - phone technology with the development of personal portable terminal has been developed crossroads. Technology-based detection of 3D face recognition technology that recognizes objects detected through the intelligent video recognition technology has been evolving technologies based on image recognition, face detection technology with through the development speed is booming. In this paper, based on human face recognition technology to detect the object recognition image processing technology is applied through the face recognition technology applied to the IP camera is the party of the mouth, and allowed the ability to identify and apply the human face recognition, measurement techniques applied research is suggested. Study plan: 1) face model based face tracking technology was developed and applied 2) algorithm developed by PC-based measurement of human perception through the CPU load in the face value of their basic parameters can be tracked, and 3) bilateral distance and the angle of gaze can be tracked in real time, proved effective.