• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.670-675
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• 2012

If the region of interest (ROI) is set within the picture of image and video and the high quality is provided in ROI compared to Non ROI, then overall subjective picture quality can be increased. ROI extracted by the color camera only increases the calculation complexity and reduces the extraction accuracy. In this paper, we use depth camera to set the ROI and calculate the object distance from camera, then propose a method that the different picture quality is controlled by depending on the distance of an object. That is, we apply a high quantization step size to the far object, but relatively a low quantization step size to the close object, so better picture quality can be provided. Simulation results show that applying the differential quantization step size to the distance of objects by the proposed method can improve the subjective picture quality.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.271-277
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• 2017

In the image processing, foreground image extraction is mainly applied to recognize a moving object or an object. In the game, the objects included in the foreground image can be mainly characters, non player characters, items, and the like. These objects can be the player's primary concern with objects that are the target of players' movement, attack, defense, and collection. In this background, this research is a study to extract players' interest areas. To this end, first, the foreground image is extracted. Second, the extracted foreground image is accumulated for a certain period of time, and the image is displayed as a result image. The accumulated foreground image according to the play time helps to know the location and frequency of screen appearance of game objects. This study can help players design their interest areas and design an efficient UX/UI.

• Proceedings of the KSR Conference
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• 2003.10c
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• pp.587-593
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• 2003

There has been much interest in the Bluetooth technology since it could enable users to connect to a wide range of computing and telecommunication devices without the need to carry or connect cables. It delivers opportunities for rapid, ad-hoc connections, and in the future, could possibly enable automatic, unconscious, connections between devices. In this paper, we discussed a scatternet formation protocol for Bluetooth-based ad hoc networks and proposed the identification system of an object using Bluetooth Scatternets. Over the past few years, several studies have been made on the identification of an object by several RF(Radio Frequency) systems. But there are still some problems, the interference of signals as an example, for the identification of an object. The critical question is how to identify an object precisely without the interference of signals. This paper is an investigation of the Scatternet formation protocol for Bluetooth-based ad hoc networks and the identification system of an object using Bluetooth Scatternets composed of multiple Piconets.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.139-146
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• 2009

This paper describes how a person extracts a unknown object with pointing gesture while interacting with a robot. Using a stereo vision sensor, our proposed method consists of two stages: the detection of the operators' face, the estimation of the pointing direction, and the extraction of the pointed object. The operator's face is recognized by using the Haar-like features. And then we estimate the 3D pointing direction from the shoulder-to-hand line. Finally, we segment an unknown object from 3D point clouds in estimated region of interest. On the basis of this proposed method, we implemented an object registration system with our mobile robot and obtained reliable experimental results.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.17-19
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• 2007

This paper describe an interactive video object segmentation tool which can be used to generate MPEG-4 video object planes for multimedia broadcasting and enables content based functionalities. In order to apply these functionalities, each frame of video sequence should be represented in terms of video objects. Semiautomatic segmentation can be thought of as a user-assisted segmentation technique. A user can initially mark objects of interest around the real object boundaries. Then the user-guided and selected objects are continuously separated from the unselected areas though time evolution in the image sequences. We proposed method shows very promising result and this encourages the development of object based video editing system.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.374-385
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• 2020

In this paper, we propose a preprocessing technique to solve the problems of action recognition with Equirectangular Projection (ERP) video. The preprocessing technique proposed in this paper assumes the person object as the subject of action, that is, the Object of Interest (OOI), and the surrounding area of the OOI as the ROI. The preprocessing technique consists of three modules. I) Recognize person object in the image with object recognition model. II) Create a saliency map from the input image. III) Select subject of action using recognized person object and saliency map. The subject boundary box of the selected action is input to the action recognition model in order to improve the action recognition performance. When comparing the performance of the proposed preprocessing method to the action recognition model and the performance of the original ERP image input method, the performance is improved up to 99.6%, and the action is obtained when only the OOI is detected. It can also see the effects of related video summaries.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.317-320
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• 2005

The LBS (Location-Based Services) are valuable information services combined the location of moving object with various contents such as map, POI (point of Interest), route and so on. The must general service of LBS is route determination service and its applicable parts are FMS (Fleet Management System), travel advisory system and mobile navigation system. The core function of route determination service is determination of optimal route from source to destination in various environments. The MODB (Moving Object Database) system, core part of LBS composition systems, is able to manage current or past location information of moving object and massive trajectory information stored in MODB is value-added data in CRM, ERP and data mining part. Also this past trajectory information can be helpful to determine optimal route. In this paper, we suggest methods to determine optimal route by querying past trajectory information in MODB system and verify the effectiveness of suggested method.