• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2075-2092
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• 2017

Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.165-175
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• 2008

Currently, software development methods have been advanced to service-oriented from component-oriented, to component-oriented from object-oriented. The component-oriented and service-oriented software development methods are analyzed by object-oriented UML model. So, the efficient analysis method for object-oriented UML model needs. In this paper, we suggest the analysis guideline and process based on event using Input Data-Process-Output Data Table for identifying use cases and classes efficiently. And the suggested method complements the problems depending the developer's perspective and experience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.289-292
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• 2007

An object color identification and classification embedded system realization for uninhabited stock management is presented in this paper. The embedded system is realized by using ultrasonic sensor to extract the object and distance, and detecting binary image from USB CCD camera. The algorithm is identified by comparing the reference pattern with the color pattern of input image, and move to the settled rack at the store. The experimental result leads to use the uninhibited stock management with practice as a robot.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.10-18
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• 2022

Since High Sierra, APFS has been used as the main file system. It is a well-established file system that has been used stably thus far. From the perspective of digital forensics, there are still many areas to be investigated. Apple File System Reference is provided to the apple developer site, but it is not satisfactory to fully analyze APFS. Researchers know more about the structure of APFS than before, but they have not yet fully analyzed its structure to a perfect level about it. In this paper, we develop APFS object identification tool for digital forensics. The most basic and essential object identification and analysis of the APFS filesystem will be conducted with the tool. The analysis in this study serves as the background for an analysis of the checkpoint operation principle and structure, including the more complex B-tree structure of APFS. There are several options for the developed tool, but the results of two use cases will be shown here. Based on the implemented tool, it is hoped that more functions will be added to make APFS a useful tool for faster and more accurate analyses.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.63-71
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• 1997

In this paper, we describe an approach that determines the identity of surfaces of an object with planar and curved surfaces from range data of the object in the scene. The proposed matching scheme presents that surface correspondence of an object is achieved by simple comparison of values for representing surfaces of the object with model in order to avoid unnecessary matching procedures. We use uniquely assigned Surface Representing Value(SRV) for representing surfaces of the object, which are sums of all weighted view-point independent features. And, the proposed method is simple, quite effective and insensitive to occlusion and noise in sensor data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Journal of the Semiconductor & Display Technology
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• v.11 no.4
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• pp.49-55
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• 2012

This paper proposes an efficient method of object identification and localization for image recognition. The new proposed algorithm utilizes correlogram back-projection in the YCbCr chromaticity components to handle the problem of sub-region querying. Utilizing similar spatial color information enables users to detect and locate primary location and candidate regions accurately, without the need for additional information about the number of objects. Comparing this proposed algorithm to existing methods, experimental results show that improvement of 21% was observed. These results reveal that color correlogram is markedly more effective than color histogram for this task. Main contribution of this paper is that a different way of treating color spaces and a histogram measure, which involves information on spatial color, are applied in object localization. This approach opens up new opportunities for object detection for the use in the area of interactive image and 2-D based augmented reality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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• pp.116-123
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• 2008

Food and Agriculture Organization (FAO) and many countries make an effort to conserve and utilization of animal genetic resources to prepare for our unpredictable future. In order to protect the customer and the producer from the animal diseases and unjust distribution, many country seek to appropriate solution. Among the solutions, RFID technology can be used as a basic technology, since this technology can be applied in the conservancy and utilization of animal genetic resources, object management for improved animal and traceability of animal's distribution flow. There are two main issues in making the efficient RFID environment. The first issue is the standardization of code system for object identification. International Organization for Standard (ISO) published the standard which regulates RFID of animal (ISO 11784 and ISO 11785). Based on these standards, many countries have tried to establish their national standard. In Korea, National Institute of Animal Science (NIAS) playa main role in establishing the standard of object identification code based on ISO 11784. Even though the standard format of object's identification is well established, the RFID system may not be operated well without the standardization of RFID network and related equipment. In Korea, National Internet Development Agency of Korea (NIDA) has proposed the RFID Network at 2006, which can be applied in the different kind of system at each phase. But, the implementation case of this RFID Network does not reported yet, since many company or agency who introduce RFID technology, implemented as an isolated individual system. In our study, we show that RFID network can be utilized for any kind of system at each phase, and propose the improvement point in order to be widely used.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.51-59
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• 2024

In this work, we focused on reducing the amount of image data to be sent by extracting and progressively sending prominent image features to high-performance computing systems taking into consideration the right amount of image data required by object identification application. We demonstrate that with our technique called Progressive Object Detection over a Lossless Network using Fragmented DCT Coefficients (Proficient), object identification applications can detect objects with at least 70% combined confidence level by using less than half of the image data.