• Journal of Korean Ophthalmic Optics Society
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• v.20 no.4
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• pp.405-414
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• 2015

Purpose: We analyse characteristics of optical shop customer's segmented market by using clustering analysis, and we expect it would be a useful indicator of marketing strategy for optical shops. Methods: Survey was conducted from March 10 to March 31, 2015. The survey asked customers who have visited optical shops in Seoul and Northern Gyeonggi-do regions, and analyzed by utilizing SPSS v.10.0 statistical package program. The analysing methods are frequency analysis, factor analysis about variable of values, clustering analysis for market segmentation, and crosstabs. Results: The market is segmented based on values. In the process of establishing marketing strategy, it is useful to establish strategy by classifying customers into 3 types of cluster; "middle level value oriented cluster", "high level value oriented cluster", "high level value oriented and non-religious cluster". In marketing strategy of progressive lenses, it turned out that the most important strategy is to target self-employed person in "middle level value oriented cluster". Conclusions: As a result of market segmentation by using clustering analysis, it was classified into 3 types of cluster, and we found that most important customer for progressive lenses is self-employed person in "middle level value oriented cluster" who is more than 41 years old.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.913-924
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• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.68-73
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• 2005

Various techniques have been proposed for detection and tracking of targets in order to develop a real-world computer vision system, e.g., visual surveillance systems, intelligent transport systems (ITSs), and so forth. Especially, the idea of distributed vision system is required to realize these techniques in a wide-spread area. In this paper, we develop a ubiquitous vision system for location-awareness of multiple targets. Here, each vision sensor that the system is composed of can perform exact segmentation for a target by color and motion information, and visual tracking for multiple targets in real-time. We construct the ubiquitous vision system as the multiagent system by regarding each vision sensor as the agent (the vision agent). Therefore, we solve matching problem for the identity of a target as handover by protocol-based approach. We propose the identified contract net (ICN) protocol for the approach. The ICN protocol not only is independent of the number of vision agents but also doesn't need calibration between vision agents. Therefore, the ICN protocol raises speed, scalability, and modularity of the system. We adapt the ICN protocol in our ubiquitous vision system that we construct in order to make an experiment. Our ubiquitous vision system shows us reliable results and the ICN protocol is successfully operated through several experiments.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.955-958
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• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.

• Journal of Multimedia Information System
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• v.7 no.3
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• pp.197-204
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• 2020

Superpixel methods are widely used in the preprocessing stage as a method to reduce computational complexity by simplifying images while maintaining the characteristics of the images in the computer vision applications. It is common to generate superpixels of similar size and shape based on the pixel values rather than considering the characteristics of the image. In this paper, we propose a method to control the sizes and shapes of generated superpixels, considering the contents of an image. The proposed method consists of two steps. The first step is to over-segment an image so that the boundary information of the image is well preserved. In the second step, generated superpixels are merged based on similarity to produce the target number of superpixels, where the shapes of superpixels are controlled by limiting the maximum size and the proposed roundness metric. Experimental results show that the proposed method preserves the boundaries of the objects in an image more accurately than the existing method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2780-2782
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• 2005

In this paper, we present a mobile robot localization solution by using a Ubiquitous Vision System (UVS). The collective information gathered by multiple cameras that are strategically placed has many advantages. For example, aggregation of information from multiple viewpoints reduces the uncertainty about the robots' positions. We construct UVS as a multi-agent system by regarding each vision sensor as one vision agent (VA). Each VA performs target segmentation by color and motion information as well as visual tracking for multiple objects. Our modified identified contractnet (ICN) protocol is used for communication between VAs to coordinate multitask. This protocol raises scalability and modularity of thesystem because of independent number of VAs and needless calibration. Furthermore, the handover between VAs by using ICN is seamless. Experimental results show the robustness of the solution with respect to a widespread area. The performance in indoor environments shows the feasibility of the proposed solution in real-time.

• Culinary science and hospitality research
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• v.12 no.3 s.30
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• pp.61-74
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• 2006

The objective of this study are to examine how the factors influence each other by determining the appropriate measurement standard based on the Dining-out Motives, restaurant attribute evaluation, intention of word of mouth and reusing, an effective restaurant marketing strategy on the basis of the analytical results by patrons and market segmentations. The study surveyed 321 subjects and processed the result using SPSS for Win. V. 12.1. For statistical analysis, Frequency, Factor Analysis, and Regression were put into operation. The results showed that dining-out motives and restaurant attribute evaluation had positive effects on the intention of word of mouth and reusing. Furthermore, the restaurant owners or managers will need to understand the existing market and target markets more objectively, and, through this market segmentation, formulate a marketing strategy that is appropriate for diverse desires of customers and different characteristics of restaurants.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.16-22
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• 2018

This paper presents a solution for personal profiling system based on user-oriented tracking. Here, we introduce a new way to identify and track humans by using two types of cameras: dome and face camera. Dome camera has a wide view angle so that it is suitable for tracking human movement in large area. However, it is difficult to identify a person only by using dome camera because it only sees the target from above. Thus, face camera is employed to obtain facial information for identifying a person. In addition, we also propose a new mechanism to locate human on targeted location by using grid-cell system. These result in a system which has the capability of maintaining human identity and tracking human activity (movement) effectively.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.39-52
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• 2001

Recently, the assessment of a bank efficiency focusing on its branches has been conceived as important in developing a competitive strategy. DEA (Data Envelopment Analysis) model can be employed as an effective analysis model for such an assessment. Therefore, this paper proposes an analysis process using DEA model to conduct an efficiency assessment of bank branches. The proposed process includes a segmentation of branches considering their competitive environment and strategy for target market : this approach can help to develop effective strategies for each group of branches. The proposed DEA model can analyze efficiency in terms of not only cost but also marketing. Finally, a real case is analyzed, demonstrating the effectiveness of the proposed model and process.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.307-312
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• 2001

In this paper, we proposed the object-tracking algorithm that recognizes and estimates the any shaped and size objects using vision system. For the extraction of the object from the background of the acquired images, spatio-temporal filter and signature parsing algorithm are used. Specially, for the solution of correspondence problem of the multiple objects tracking, we compute snake energy and position information of the target objects. Through the real-time tracking experiment, we verified the effectiveness of the suggested tracking algorithm.