• Korean Institute of Interior Design Journal
• /
• v.21 no.4
• /
• pp.87-95
• /
• 2012

This study is for the analysis to which element of space the users observing the lobby at a public space pay more attention for their visual perception. It is focused on the typology process of observation characters. The subjects, in the observation process, came to be interested in the circumstantial clues for space perception and the detailed characters drawing their interest. I could analyze the observation characters of the subjects observing the space by the comprehension and typology of their observation characters. First, from the viewpoint of successive 9 times of observations, each subject observed for 0.32 second to get the visual perception in the applied space, but spent another 0.39 second for the exploration of another observation object or the space roaming. The observation character of the subjects at the lobby of the public space selected for this experiment was that they spent more time on space exploration than on concentration on a point in the space. Second, I analyzed the typology process through the time range. Since the subjects' frequency varied depending on the way to set up the time range, the necessity was proposed that the time range for the analysis of observation characters should be set up more objectively. Third, in case of analyzing the observation characters by 10-second-unit time range, the concentration in the beginning and the middle was 25%, and that in the beginning and the final 41.7%, which showed that 75% of the subjects concentrated in the beginning of the observation time when the concentration in the beginning is added to it. Fourth, the type 3 categorized as "concentration in the beginning and the middle" is the group 47.1 percent of the subjects belong to, and each subject concentrated 1.1 times in the beginning and 2.1 times in the final, which showed that the concentration in the final was 1.75 times as high as that in the beginning.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.2 no.1
• /
• pp.84-88
• /
• 2010

Recently, it is essential to have the system which can track down and identity the random object in the space in which security is a high priority. Due to the fact that we mentioned above, in this paper. We suggest the intelligent video surveillance system effective image-process-education in this paper. The experiment was conducted to check and track down the entering vehicle. And, Pan-Tilt-Zoom camera was used to obtain the enlarged image of the object while a vehicle was making stop in target area. As a result, the experiment has shown the data as following. When the object is in motion, success rate is 97.4%, while success rate is 91% when the object is motionless. By using the suggested system, effective image-process-education is should be achieved because the students who participate in the class can have simultaneous access to the system for real time image data and camera control.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4438-4460
• /
• 2017

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.7
• /
• pp.75-82
• /
• 2022

There are various exhibition halls, shopping malls, theme parks around us and analysis of interest in exhibits or contents is mainly done through questionnaires. These questionnaires are mainly depend on the subjective memory of the person being investigated, resulting in incorrect statistical results. Therefore, it is possible to identify an exhibition space with low interest by tracking the movement and counting the number of visitors. Based on this, it can be used as quantitative data for exhibits that need replacement. In this paper, we use deep learning-based artificial intelligence algorithms to recognize visitors, assign IDs to the recognized visitors, and continuously track them to identify the movement path. When visitors pass the counting line, the system is designed to count the number and transmit data to the server for integrated management.

• Journal of Broadcast Engineering
• /
• v.25 no.5
• /
• pp.770-775
• /
• 2020

Since 360-degree ERP frame structure has location-dependent distortion, existing video surveillance algorithms cannot be applied to 360-degree video. In this paper, an activated viewport based event detection method is proposed for 360-degree video. After extracting activated viewports enclosing object candidates, objects are finally detected in the viewports. These objects are tracked in 360-degree video space for region-based event detection. The proposed method is shown to improve the recall and the false negative rate more than 30% compared to the conventional method without activated viewports.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.5
• /
• pp.637-644
• /
• 2021

In general, in the fields of computer vision, robotics, and augmented reality, the importance of 3D space and 3D object detection and recognition technology has emerged. In particular, since it is possible to acquire RGB images and depth images in real time through an image sensor using Microsoft Kinect method, many changes have been made to object detection, tracking and recognition studies. In this paper, we propose a method to improve the quality of 3D reconstructed images by processing images acquired through a depth-based (RGB-Depth) camera on a multi-view camera system. In this paper, a method of removing noise outside an object by applying a mask acquired from a color image and a method of applying a combined filtering operation to obtain the difference in depth information between pixels inside the object is proposed. Through each experiment result, it was confirmed that the proposed method can effectively remove noise and improve the quality of 3D reconstructed image.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.04a
• /
• pp.393-398
• /
• 2002

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. forthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.253-257
• /
• 2004

Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.11a
• /
• pp.422-427
• /
• 2006

This paper presents force-feedback control performance of a haptic device in virtual environment of minimally invasive surgery(MIS). As a first step, based on an electrorheological(ER) fluid and spherical geometry, a new type of master device is developed and integrated with a virtual environment of MIS such as a surgical tool and human organ. The virtual object is then mathematically formulated by adopting the shape retaining chain linked(S-Chain) model. After evaluating reflection force, computational time, and compatibility with real time control, the virtual environment of MIS is formulated by interactivity with the ER haptic device in real space. Tracking control performances for virtual force trajectory are presented in time domain, and theirtrackingerrorsareevaluated.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.12 s.117
• /
• pp.1286-1293
• /
• 2006

This paper presents force-feedback control performance of a haptic device in virtual environment of minimally invasive surgery(MIS). As a first step, based on an electrorheological (ER) fluid and spherical geometry, a new type of master device is developed and integrated with a virtual environment of MIS such as a surgical tool and human organ. The virtual object is then mathematically formulated by adopting the shape retaining chain linked(S-chain) model. After evaluating reflection force, computational time, and compatibility with real time control, the virtual environment of MIS is formulated by interactivity with the ER haptic device in real space. Tracking control performances for virtual force trajectory are presented in time domain.