• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.9
• /
• pp.39-48
• /
• 2009

Human face tracking has gradually become an important issue in applications for portable multimedia devices such as digital camcorder, digital still camera and cell phone. Current embedded face tracking software implementations lack the processing abilities to track faces in real time mobile video processing. In this paper, we propose a power efficient hardware-based face tracking architecture operating in real time. The proposed system was verified by FPGA prototyping and ASIC implementation using Samsung 65nm CMOS process. The implementation result shows that tracking speed is less than 8.4 msec with 150K gates and 20 mW average power consumption. Consequently it is validated that the proposed system is adequate for portable multimedia device.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.7
• /
• pp.34-42
• /
• 1999

Multi-target tracking system is defined as tracking several targets simultaneously. Kalman filter is widely used for target tracking problems. Kalman filter is known to be extremely useful as an optimal estimator but has a shortcoming of computational complexity. So a simplified estimator model which had less computational burden is proposed for a real-time implementation of multi-target tracking systems. In this paper, Kalman filter is applied to implement a real-time tracking system with a simplified target model. The proposed Kalman filter model is simpler compared with those of conventional ones, greatly reducing computation time, yet keeping the tracking abilities of the optimal Kalman filter. Through both simulations and experiments with real environments, it is demonstrated that the proposed simplified model works good in real situation with multiple to be tracked.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.25-29
• /
• 1997

In this thesis, we construct the microrobot succor system and navigate the real-time path planning and visual tracking of each robot. The system consists robots, vision system and a host computer. Because the robots are free-ranging mobile robot, it is needed to make and gallow the path. The path is planned and controlled by a host computer, ie. Supervisory control system. In path planning, we suggest a cost function which consists of three terms. One is the smoothness of the path, another is the total distance or time, and the last one is to avoid obstacles. To minimize the cost function, we choose the parametric cubic spline and update the coefficients in real time. We perform the simulation for the path planing and obstacle avoidance and real experiment for visual tracking

• Journal of Information Technology Services
• /
• v.10 no.1
• /
• pp.105-116
• /
• 2011

With recent spotlight on the, uniquitous computing technology, the need for object of indentification and location infrastructure has increased. Such GPS technolgy must utilize IEEE 802.15.4 Zigbee used for existing wireless sensor network infra as a basice element for user's context-awareness in a uniquitous environement, for effectiveness.Such real-time GPS service is provided in the internal environment where the user would actually are and most high-rise buildlings apply. Underthe assumption, the real-time GPS technology is seperated by each floor, and signals do not get transmitted to other floors, the application on one floor within the high-rise buildling was conducted. This study intends to suggest a floor detection algorithm using IEE 802.15.3/Zigbee's RSSI which supports the accuracy within a couple of meters for the user's the movement between the floors in high-rise buildings in a complex environment. It proposes an floor detection algorithm using IEEE 802.15.4/Zigbee's RSSI which provides accuracy within a radius of few meters for the users movement between the floors for real-time location tracking within high-rise building in a cmoplex environment. Furthermore, for more accurate real-time location tracking, it suggests an algorithm for real-time location tracking using IEEE 802.15.4a/Zigbee's CSS technology based on triangulation. Based on the suggested algorithm, it designs a hybrid real-time location tracking service system in a high-rise buildling and test its functions.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2358-2361
• /
• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks which have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, this paper first has a global search of entire image and tracks the object through local search when the object is recognized.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.70.1-70
• /
• 2001

Recently, research of visual control is getting more essential in robotic application, and acquiring 3D informations from the 2D images is becoming more important with development of vision system. For this application, we propose the effective way of controlling stereo vision tracking system for target tracking and calculating distance between target and camera. In this paper we address improved controller using dual-loop visual servo which is more effective compared with using single-loop visual servo for stereo vision tracking system. The speed and the accuracy for realizing a real time tracking are important. However, the vision processing speed is too slow to track object in real time by using only vision feedback data. So we use another feedback data from controller parts which offer state feedback ...

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.493-496
• /
• 2009

Many AR (Augmented Reality) applications have been interested in a marker-less tracking since the tracking methods give camera poses without attaching explicit markers. In this paper, we propose a new marker-less page recognition and tracking algorithm for an AR book application such as DigilogBook. The proposed method only requires orthogonal images of pages, which need not to be trained for a long time, and the algorithm works in real-time. The page recognition is done in two steps by using SIFT (Scale Invariant Feature Transform) descriptors and the comparison evaluation function. And also, the method provides real-time tracking with 25fps ~ 30fps by separating the page recognition and the frame-to-frame matching into two multi-cores. The proposed algorithm will be extended to various AR applications that require multiple objects tracking.

• Journal of Korea Multimedia Society
• /
• v.22 no.2
• /
• pp.167-177
• /
• 2019

Even though so much progresses have been achieved in Multiple Object Tracking (MOT), most of reported MOT methods are not still satisfactory for commercial embedded products like Pan-Tilt-Zoom (PTZ) camera. In this paper, we propose a real-time multiple pedestrians tracking method for embedded environments. First, we design a new light weight convolutional neural network(CNN)-based pedestrian detector, which is constructed to detect even small size pedestrians, as well. For further saving of processing time, the designed detector is applied for every other frame, and Kalman filter is employed to predict pedestrians' positions in frames where the designed CNN-based detector is not applied. The pose orientation information is incorporated to enhance object association for tracking pedestrians without further computational cost. Through experiments on Nvidia's embedded computing board, Jetson TX2, it is verified that the designed pedestrian detector detects even small size pedestrians fast and well, compared to many state-of-the-art detectors, and that the proposed tracking method can track pedestrians in real-time and show accuracy performance comparably to performances of many state-of-the-art tracking methods, which do not target for operation in embedded systems.

• Journal of the Korean Society for Precision Engineering
• /
• v.24 no.10
• /
• pp.64-74
• /
• 2007

Because of the size and environment in the shipbuilding process, the portable type robot is required for the automatic seam tracking. For this reason, the structure of laser sensor should be considered in the initial design step and the coordinate transformation between welding robot and laser sensor, which is joint finder, must be identified exactly and the real time tracking algorithm based on these consideration could be developed. In this research, laser displacement sensor in which its structure is laser beam's vertical projection, is developed to recognize the location of weld joint. In practical applications, however, images of weld joints are often degraded because of the surface specularity or spatter. To overcome the problem, the constrained joint finding algorithm is proposed. In the approach of coordinate conversion rule for the visual feedback control among welding torch, robot body and laser sensor is applied by the same reference point method. In the real time seam tracking algorithms we propose constrained sampling method which uses look ahead distance. The RLS(Recursive Least Square) filter is applied to obtain the smooth tracking path from the sensitive edge data. From the experimental results, we could see the possibility that the developed laser sensor with proposed processing algorithm and real time seam tracking method can be used as a welding under the shipbuilding condition.

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