• Journal of Korea Multimedia Society
• /
• v.16 no.11
• /
• pp.1261-1271
• /
• 2013

Zoom tracking involves the automatic adjustment of the focus motor in response to the zoom motor movements for the purpose of keeping an object of interest in focus, and is typically achieved by moving the zoom and focus motors in a zoom lens module so as to follow the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. Thus, one can simply implement zoom tracking by following the most closest trace curve after all the trace curve data are stored in memory. However, this approach is often prohibitive in practical implementation because of its large memory requirement. Many other zoom tracking methods such as GZT, AZT and etc. have been proposed to avoid large memory requirement but with a deteriorated performance. In this paper, we propose a new zoom tracking method called 'Approximate Feedback Zoom Tracking method (AFZT)' on DM36x-based IP network camera, which does not need large memory by approximating nearby trace curves, but generates better zoom tracking accuracy than GZT or AZT by utilizing focus value as feedback information. Experiments through real implementation shows the proposed zoom tracking method improves the tracking performance and works in real-time.

• ETRI Journal
• /
• v.46 no.3
• /
• pp.421-431
• /
• 2024

In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation of the noise subspace is performed according to the NC characteristics. Because the proposed method uses the signal information from the previous iteration, it can realize automatic data associations. Compared with traditional DPD and two-step localization methods, our novel process has lower computational complexity and provides higher accuracy. Moreover, its performance is better than that of the traditional tracking methods. Numerous simulation results support the superiority of our proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.5
• /
• pp.1400-1420
• /
• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1244-1248
• /
• 2003

This paper describes visual tracking procedure of the underwater mobile robot for nuclear reactor vessel inspection, which is required to find the foreign objects such as loose parts. The yellowish underwater robot body tends to present a big contrast to boron solute cold water of nuclear reactor vessel, tinged with indigo by Cerenkov effect. In this paper, we have found and tracked the positions of underwater mobile robot using the two color information, yellow and indigo. The center coordinates extraction procedures are as follows. The first step is to segment the underwater robot body to cold water with indigo background. From the RGB color components of the entire monitoring image taken with the color CCD camera, we have selected the red color component. In the selected red image, we extracted the positions of the underwater mobile robot using the following process sequences; binarization, labelling, and centroid extraction techniques. In the experiment carried out at the Youngkwang unit 5 nuclear reactor vessel, we have tracked the center positions of the underwater robot submerged near the cold leg and the hot leg way, which is fathomed to 10m deep in depth.

• The Journal of Korea Robotics Society
• /
• v.8 no.4
• /
• pp.266-272
• /
• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.361-364
• /
• 2007

A small sized device with computing, communicating, sensing capability is changing our life. It will be deployed in the world and acquire a lot of data from the world. It is used for various applications such as military surveillance, environmental monitoring, structure health monitoring, building management, asset tracking, etc. In this paper we focus on USN middleware for asset tracking. A mobile asset is moving here and there within a specific area. The USN middleware tracks the mobile assets in real-time by using sensor nodes and notify their current positions to a user. To achieve the goal, the USN middleware provides some features related to the positions of mobile assets.. They are storing location data by using 3D indexing method, retrieving them by using spatio-temporal query, making trace of an asset, and retrieving the history data of an asset. In the paper, we developed USN middleware to adapt the requirements of asset tracking. It can help users increase the efficiency of their business related to mobile assets and make a valuable decision.

• Journal of Mechanical Science and Technology
• /
• v.18 no.7
• /
• pp.1236-1245
• /
• 2004

In this study, an optical imaging method was developed for the measurements of the sizes and velocities of droplets in sprays. Double-exposure single-frame spray images were captured by the imaging system. An image processing program was developed for the measurements of the sizes and positions of individual particles including separation of the overlapped particles and particle tracking and pairing at two time instants. To recognize and separate overlapping particles, the morphological method based on watershed segmentation as well as separation using the perimeter and convex hull of image was used consecutively. Better results in separation were obtained by utilization of both methods especially for the multiple or heavily-overlapped particles. The match probability method was adopted for particle tracking and pairing after identifying the positions of individual particles and it produced good matching results even for large particles like droplets in sprays. Therefore, the developed optical imaging method could provide a reliable way of analyzing the motion and size distribution of droplets produced by various sprays and atomization devices.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.642-645
• /
• 1991

This paper presents the results of research on hardware and software of the landmark tracking system to the positions of moving robot in real time. The landmark tracking system is composed of CCD camera, landmark, strobo system and image processing board. The algorithm calculates the position and direction by using the coordinate transformation fomula after calculating the centroid and rotation angle of landmark at fixed position using the image data. The experiment is performed with landmark tracking system is loaded on xyz-table. XYZ-table is used for identifying the true position in our experiment. The results shows that this system has high performance with maxima error of .+-.1 pixels.

• Journal of Advanced Navigation Technology
• /
• v.14 no.6
• /
• pp.783-790
• /
• 2010

For safety navigation of ships at sea, ships monitor their location obtained from Global Positioning Satellite System (GNSS). In this study, we computed near-real-time positions of a ship at sea using GPS Precise Point Positioning (PPP) technique and analyzed precision of the near-real-time positions. We conducted ship borne GPS observations in the south sea of Korea. To process the GPS data using PPP technique, GIPSY-OASIS (GPS Inferred Positioning System-Orbit Analysis and Simulation Software) developed by the Jet Propulsion Laboratory was used. Antenna phase center variations, ocean tidal loading displacements, and azimuthal gradients of the atmosphere were corrected or estimated as standard procedures of high-precision GIPSY-OASIS data processing. As a result, the precisions of near-real-time positions was ~1cm.

• Proceedings of the IEEK Conference
• /
• 2000.06e
• /
• pp.43-46
• /
• 2000

In this paper, we present a method for vehicle tracking systems using $\alpha$-$\beta$ filter based on fuzzy logic. The $\alpha$-$\beta$ filter estimates the future target positions using fixed $\alpha$.$\beta$ coefficients. We utilize the fuzzy logic to make $\alpha$ and $\beta$ coefficients very with the position. Comparisons of tracking performance made for three different schemes: the $\alpha$-$\beta$ filter, $\alpha$-$\beta$filter using fuzzy logic, and the kalman filter.