• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.55-62
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• 2009

This study is concerned with predicting human search performance using a visual lobe. The most previous studies on human performance in visual search have been limited to a single-target search. This study extended the visual search research to multiple-target search including targets of different types as well as targets of same types. A model for predicting visual search performance was proposed and the model was validated by human search data. Additionally, this study found that human subjects always did not use a constant ratio of the whole visual lobe size for each type of targets in visual search process. The more conspicuous the target is, the more ratio of the whole visual lobe size human subjects use. The model that can predict human performance in multiple-target search may facilitate visual inspection plan in manufacturing.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.165-171
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• 2003

Visual search in an unstructured search field is a fruitful research area for computational modeling. Search models that describe relationship between search time and probability of target detection have been used for prediction of human search performance and provision of ideal goals for search training. Until recently, however, most of models were focused on detecting a single target in a search field, although, in practice, a search field includes multiple targets and search models for multiple targets may differ from search models for a single target. This study proposed a random search model for multiple targets, generalizing a random search model for a single target which is the most typical search model. To test this model, human search data were collected and compared with the model. This model well predicted human performance in visual search for multiple targets. This paper also proposed how to determine optimal stopping time in multiple-target search.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.57-59
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• 2006

The purpose of search problem is to maximize the probability of target detection as limited search capability. Especially, as elapsing of time at a point of time of initial information received the target detection rate for searching an expected location due to a moving target such that wrecked ship or submarine decrease in these problems. The algorithm of search problem to a moving target having similar property of above targets should solve the search route as quickly as possible. In existing studies, they have a limit of applying in practice due to increasing computation time required by problem size (i.e., number of search area, search time). In this study, we provide that it takes more reasonable computation time than preceding studies even though extending a problem size practically using an approximate computation of probability.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Korean Journal of Cognitive Science
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• v.25 no.3
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• pp.211-232
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• 2014

People search a certain object or a person so many time in a day. Besides the information about what the target is, perceptual information of the target can influence on the search process. In the current study, using an eye-tracker we aimed to examine whether the perceptual information of previewing target stimuli on the visual search process of the target and the task performance. Participants had to identify the previewing target stimulus presented in the middle of the screen, and then had to search the target among 8 items presented in a circle array, and had to decide whether the size of the target in the search display was same as that of the previewing stimulus. The experimental conditions were divided into 8 within-subject conditions by whether the search display was consisted of all the same size items or different size items (homogeneous search display vs. inhomogeneous search display), by the size of the preview target stimulus, and by the size of the target stimulus in the search display. Research hypothesis is that the size information of the previewing influence on the visual search process of the target and task performance when the items in the search display are in different sizes. In the results of behavioral data analysis, the reaction time showed the main effect of the search display, and the size of the target stimulus in the search display. and the interaction between the size consistency effect of target stimulus and the search display condition. In the results of analysis of eye-movement information, the Initial Saccade to Target Ratio measurement showed the interaction between the size consistency effect of target stimulus and the search display condition as the reaction time measurement did. That is, the size consistency effect of target stimulus only in the inhomogeneous search display condition indicated that participants searched the items in the same size as that of preview target stimulus. Post-hoc analyses revealed that the search and task performance in the inhomogeneous display condition were faster when the target size was consistent, but rather slower when the target size was inconsistent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2371-2379
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• 2017

For the drone that is active in a wide search area, the time to grasp the target in the field of applications such as searching for emergency patients, monitoring of natural disasters requiring prompt warning and response, that is, the speediness of target detection is very important. In the actual operation of drone, the time for target detection is highly related to collaboration between drones and search algorithm to efficiently search the navigation area. In this research, we will provide a search method with cooperation of drone based on target existence probability to solve the problem of quickness in drone target search. In particular, the proposed method increases the probability of finding a target and shorten the search time by transmitting high-altitude drone search results to a low-altitude drone after searching first and performing more precise search. We verify the performance of the proposed method through several simulations.

• Journal of the military operations research society of Korea
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• v.35 no.1
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• pp.21-32
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• 2009

In this study, the author uses a MATLAB simulation to develop and test a generalization of the traditional Random Search model which allows both the searcher and target to move and to be in different, but overlapping, areas. Also the best evasion speed for a randomly moving target against a Systematic Search is studied.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.78-83
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• 2018

Rapidity and accuracy are important considerations when a drone is employed in a wide surveillance area to detect a target. They are more important when the scope of application is a search and rescue operation or the monitoring of natural disasters, which may require prompt warnings and response. During the actual operation of a drone, rapidity and accuracy are associated with the change in the altitude of the drone. The aim of this study is to analyze the characteristics of drones at varying altitudes and prove that altitude is a relevant factor in the performance of drones. Herein, the characteristics of the drone at varying altitudes were analyzed through several search simulations. The results suggest that a high-altitude drone is relatively advantageous compared to a low-altitude drone in a probability-based target search, and that the search altitude is also a very important and fundamental factor in target search by drones.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.13-16
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• 2004

This paper deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection award, if detected, which represents the detection priority of target and is non-increasing with time. The objective is to establish the optimal search plan which allocates the search resource effort over the search areas in each time interval in order to maximize the total detection award. In the analysis, the given problem is decomposed into intervalwise individual search problems each being treated as a single stationary target problem for each time interval. An associated iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.

• Korean Journal of Cognitive Science
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• v.26 no.3
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• pp.357-375
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• 2015

In our daily life, the probability of target prevalence in visual search varies from very low to high. However, most laboratory studies of visual search used a fixed probability of target prevalence at 50%. The present study examined the properties of information processing during visual search where the probability of target prevalence was manipulated to vary from low (20%), medium (50%), to high (80%). The search items were made of simple shape stimuli, and search accuracy, signal detection measures, and reaction times (RTs) were analyzed for characterizing the effect of target prevalence on the information processing strategies for visual search. The analyses showed that the rates of misses increased whereas those of false alarms decreased in the search condition of low target prevalence, whereas the pattern was reversed in the high prevalence condition. Signal detection measures revealed that the target prevalence shifted response criterion (c) without affecting sensitivity (d'). In addition, RTs for correct rejection responses in the target-absent trials became delayed as the prevalence increased, whereas those for hits in the target-present trials were relatively constant regardless of the prevalence. The RT delay in the target-absent trials indicates that increased target prevalence made the 'quitting threshold' for search termination more conservative. These results support an account that the target prevalence effect in visual search arises from a shift of decision criteria and the subsequent changes in search information processing, while rejecting the account of a speed-accuracy tradeoff.