• Journal of the Optical Society of Korea
• /
• v.5 no.4
• /
• pp.140-145
• /
• 2001

We present a new method of volumetric interferometer, which is intended to measure the three-dimensional coordinates of a moving object in a simultaneous way with a single optical setup. The method is based on the principles of phase-measuring interferometry with phase shifting. Two diffraction point sources, which are made of the polished ends of single-mode optical fibers are embedded on the object. Two spherical wavefronts emanate from the diffraction point sources and interfere with each other within the measurement volume. One wavefront is phase-shifted by elongating the corresponding fiber using a PZT extender. A CCD array sensor fixed at the stationary measurement station detects the resulting interference field. The measured phases are then related to the three-dimensional location of the object with a set of non-liner equations of Euclidean distance, from which the complete set of three-dimensional spatial coordinates of the object is determined through rigorous numerical computation based upon the least square error minimization.

• Journal of Information Processing Systems
• /
• v.13 no.5
• /
• pp.1277-1298
• /
• 2017

Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.5
• /
• pp.439-448
• /
• 2022

MV (Moving Vehicle) detection using satellite imagery is important for traffic monitoring and provides a wide range of observations. Specifically, MV detection methods utilizing the time lag in single-pass optical satellite images have been studied for detecting MVs from a single set of images. Because of limitations in detecting MVs outside of roads, most previous studies required road information to limit the moving object to cars on the road. However, it is difficult to obtain road information from inaccessible areas. Therefore, this study proposed a new method for detecting MVs regardless of their locations from single-pass optical satellite images without using additional data. WV-3 (Worldview-3) satellite images were used, and a spatial correlation coefficient map was proposed to detect spatial displacement which denotes MVs across two WV-3 MS images. Finally, evaluation was performed through quantitative metrics and visual inspection. The evaluation results revealed that the proposed method can detect MV movements from the single-pass satellite images. On the contrary, misdetected or undetected MVs due to radiometric differences between the images could be identified by visual inspection. The performance of the proposed method can be improved by minimizing radiometric variations and adding conditions that are robust to radiometric differences between the images.

• Journal of Korea Multimedia Society
• /
• v.20 no.6
• /
• pp.893-910
• /
• 2017

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.

• Journal of Advanced Navigation Technology
• /
• v.17 no.1
• /
• pp.98-106
• /
• 2013

In this paper, we propose a moving object detection and tracking method for multi-view camera environment. Based on the similarity and characteristics of motion vectors and coding block modes extracted from compressed bitstreams, validation of moving blocks, labeling of the validated blocks, and merging of neighboring blobs are performed. To continuously track objects for temporary stop, crossing, and overlapping events, a window based object updating algorithm is proposed for single- and multi-view environments. Object detection and tracking could be performed with an acceptable level of performance without decoding of video bitstreams for normal, temporary stop, crossing, and overlapping cases. The rates of detection and tracking are over 89% and 84% in multi-view environment, respectively. The rates for multi-view environment are improved by 6% and 7% compared to those of single-view environment.

• Journal of Broadcast Engineering
• /
• v.28 no.1
• /
• pp.124-131
• /
• 2023

Object detection techniques are increasingly used to obtain information on physical characteristics or situations of a specific area from remote images. The accuracy of object detection is decreased in remote sensing images with low resolution because the low resolution reduces the amount of detail that can be captured in an image. A single neural network is proposed to joint the super-resolution method and object detection method. The proposed method constructs a deep residual-based network to restore object features in low-resolution images. Moreover, the proposed method is used to improve the performance of object detection by jointing a single network with YOLOv5. The proposed method is experimentally tested using VEDAI data for low-resolution images. The results show that vehicle detection performance improved by 81.38% on mAP@0.5 for VISIBLE data.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2705-2708
• /
• 2003

In this paper, we propose a method that applies matrix decomposition technique to the connection of actuator capabilities of each robot to object acceleration limits for multiple cooperative robot systems. The robot systems under consideration are composed of several robot manipulators and each robot contacts a single object to carry the object while satisfying the constraints described in kinematics as well as dynamics. By manipulating kinematic and dynamic equations of both robots and objects, we at first derive a matrix relating joint torques with object acceleration, manipulate the null space of the matrix, and then we decompose the matrix into three parts representing indeterminancy, connectivity, and redundancy. With the decomposed matrix we derive the boundaries of object accelerations from given joint actuators. To show the validity of the proposed method some examples are given in which the results can be expected by intuitive observation.

• 한국HCI학회:학술대회논문집
• /
• 2006.02a
• /
• pp.884-892
• /
• 2006

This paper describes a framework for multimodal object manipulation in virtual environments. The gist of the proposed framework is the semantic integration of multimodal input using spatial ontology and user context to integrate the interpretation results from the inputs into a single one. The spatial ontology, describing the spatial relationships between objects, is used together with the current user context to solve ambiguities coming from the user's commands. These commands are used to reposition the objects in the virtual environments. We discuss how the spatial ontology is defined and used to assist the user to perform object placements in the virtual environment as it will be in the real world.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.50.5-50
• /
• 2002

In this paper, we propose a method using neural network (NN) to improve the motion control of a decentralized control system for cooperative transportation. In our former work, a decentralized control system for transporting a single object by multiple nonholonomic mobile robots has been developed. One of these mobile robots acts as a leader, who is assumed to be able to plan and to manipulate the omnidirectional motion of the object. Other robots, referred to as followers, cooperatively transport the object by keeping a constant position relative to the object. in this work, it is assumed that the leader can not only plan but also broadcast the local velocity of the object. Then...

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.492-495
• /
• 1997

This paper aims to derive a mathematical model of the dynamics of handling task in field robot which stable grasping and manipulates a rigid object with some dexterity. Firstly, a set of differential equation describing dynamics of the manipulators and object together with geometric constraints of tight area-contacts on motion of the overall system is analyzed and a method of computer simulation for overall system of differential-algebraic equations is presented. Thirdly, simulation results are shown and the effects of geometric constraints of contact-area are discussed. Finally, it is shown that even in the simplest case of dual single D.O.F. manipulators there exists a sensory feedback from sensing data of he rotational angle of the object to command inputs to joint actuators and this feedback connection from sensing to action eventually realizes secure grasping of the object, provided that he object is of rectangular shape and motion is confined to a horizontal