• Journal of Industrial Technology
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• v.29 no.A
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• pp.47-54
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• 2009

In this paper, we proposed hand detection and hand gesture recognition from USB camera video. Firstly, we extract hand region extraction using skin color information from a difference images. Background image is initially stored and extracted from the input images in order to reduce problems from complex backgrounds. After that, 16-directional chain code sequence is computed from the tracking of hand motion. These chain code sequences are compared with pre-trained models using DP matching. Our hand gesture recognition system can be used to control PowerPoint slides or applied to multimedia education systems. We got 92% hand region extraction accuracy and 82.5% gesture recognition accuracy, respectively.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.204-212
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• 2020

For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.43 no.4
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• pp.347-354
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• 2007

This paper describes on the real-time monitoring of net setting and hauling process for fishing operations of Danish seine vessels in the southern waters of Korea as an application of a PC based ECDIS system. Tracking of fishing process was performed for the large scale Danish seine vessel of G/T 90 and 350 PS class using the fishing gear which the length of net, ground rope, head rope and sweep line including warp in both sides were 86m, 104m, 118m and 3,200m, respectively. Tracking information for net setting and hauling process was continuously recorded for 23 fishing operations performed on November and December, 2003. All measurement data, such as trawl position, heading, towing course and past track which was individually time stamped during data acquisition, was processed in real time on the ECDIS and displayed simultaneously on the ENC chart. The results indicated that after the separation of a marker buoy from Danish seiner, the averaged running speed of vessel and the averaged setting period while shooting the seine on the course of diamond shape to surround the fish school in the 23 fishing operations were 8.3 knots and 13.1 minutes, respectively. And with the maker buoy taken on board, the averaged running speed of vessel and the averaged towing period while closing the seine on the straight route was 1.0 knots and 47.0 minutes, respectively. After the closing stage of hand rope, the hand rope was towed by the averaged speed of 2.2 knots during the 13.0 minutes. The average area for route of diamond shape swept by sweep lines of the seine in 23 fishing grounds was $709,951.6m^2$. Further investigation is also planed to provide more quantitative tracking information and to achieve more effective surveillance and control of Danish seine vessels in EEZ fishing grounds.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.22-28
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• 2019

This paper presents a method for detection of an emergency signal expressed by arm gestures based on motion segmentation and face area detection in the surveillance system. The important indicators of emergency can be arm gestures and voice. We define an emergency signal as the 'Help Me' arm gestures in a rectangle around the face. The 'Help Me' arm gestures are detected by tracking changes in the direction of the horizontal motion vectors of left and right arms. The experimental results show that the proposed method successfully detects 'Help Me' emergency signal for a single person and distinguishes it from other similar arm gestures such as hand waving for 'Bye' and stretching. The proposed method can be used effectively in situations where people can't speak, and there is a language or voice disability.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.109-116
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• 2011

In this paper, we introduce non-touch style interface system technology without any touch style controlling mechanism, which is called as "Air-interface". To develop this system, we used the full reflection principle of infrared (IR) light and then user's hand is separated from the background with the obtained image at every frame. The segmented hand region at every frame is used as input data for an hand-motion recognition module, and the hand-motion recognition module performs a suitable control event that has been mapped into the specified hand-motion through verifying the hand-motion. In this paper, we introduce some developed and suggested methods for image processing and hand-motion recognition. The developed air-touch technology will be very useful for advertizement panel, entertainment presentation system, kiosk system and so many applications.

• Annual Conference of KIPS
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• 2018.10a
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• pp.920-922
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• 2018

This paper describes a method to classify simple circular artificial markers on surfaces of a box on the back of hand to detect the pose of user's hand for VR/AR applications by using a Leap Motion camera and two IMU sensors. One IMU sensor is located in the box and the other IMU sensor is fixed with the camera. Multi-layer Perceptron (MLP) algorithm is adopted to classify artificial markers on each surface tracked by the camera using IMU sensor data. It is experimented successfully in real-time, 70Hz, under PC environments.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.566-573
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• 2020

Computers are the most common tool when using the Internet and utilizing a mouse to select and execute objects. Eye tracking technology is welcomed as an alternative technology to help control computers for users who cannot use their hands due to their disabilities. However, the pointer execution method of the existing eye tracking technique causes many malfunctions. Therefore, in this paper, we developed a gaze tracking interface that combines voice commands to solve the malfunction problem when the upper limb disabled uses the existing gaze tracking technology to execute computer menus and objects. Usability verification was conducted through comparative experiments regarding the improvements of the malfunction. The upper limb disabled who are hand-impaired use eye tracking technology to move the pointer and utilize the voice commands, such as, "okay" while browsing the computer screen for instant clicks. As a result of the comparative experiments on the reduction of the malfunction of pointer execution with the existing gaze interfaces, we verified that our system, Eye-Voice, reduced the malfunction rate of pointer execution and is effective for the upper limb disabled to use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4491-4509
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• 2017

The present paper proposes a novel dynamic system for hand gesture recognition. The approach involved is comprised of three main steps: detection, tracking and recognition. First, the gesture contour captured by a 2D-camera is detected by combining the three-frame difference method and skin-color elliptic boundary model. Then, the trajectory of the hand gesture is extracted via a gesture-tracking algorithm based on an occlusion-direction oriented linear extrapolation predictor, where the gesture coordinate in next frame is predicted by the judgment of current occlusion direction. Finally, to overcome the interference of insignificant trajectory segments, the longest common subsequence (LCS) is employed with the aid of velocity information. Besides, to tackle the subgesture problem, i.e., some gestures may also be a part of others, the most probable gesture category is identified through comparison of the relative LCS length of each gesture, i.e., the proportion between the LCS length and the total length of each template, rather than the length of LCS for each gesture. The gesture dataset for system performance test contains digits ranged from 0 to 9, and experimental results demonstrate the robustness and effectiveness of the proposed approach.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.39-49
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• 2002

This paper proposes the MAWUPC (Motion Adaptive Weighted Unmatched Pixel Count) algorithm to track multiple objects of similar color The MAWUPC algorithm has the new method that combines color and motion effectively. We apply the MAWUPC algorithm to face and hand tracking against complex background in an image sequence captured by using single camera. The MAWUPC algorithm is an improvement of previously proposed AWUPC (Adaptive weighted Unmatched Pixel Count) algorithm based on the concept of the Moving Color that combines effectively color and motion information. The proposed algorithm incorporates a color transform for enhancing a specific color, the UPC(Unmatched Pixel Count) operation for detecting motion, and the discrete Kalman filter for reflecting motion. The proposed algorithm has advantages in reducing the bad effect of occlusion among target objects and, at the same time, in rejecting static background objects that have a similar color to tracking objects's color. This paper shows the efficiency of the proposed MAWUPC algorithm by face and hands tracking experiments for several image sequences that have complex backgrounds, face-hand occlusion, and hands crossing.