• Asia-Pacific Journal of Business
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• 제15권1호
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• pp.45-69
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• 2024

Purpose - To examine the influence of mobile visual search as a strategic technology service on consumer perceived economic value and customer commitments, which in turn affect consumer's usage intention of mobile visual search. This study also explores the moderating effect of different levels of consumer online shopping orientation. Design/methodology/approach - One-by-one open-ended in-depth interview was first undertaken to 15 Korean consumers to figure the features of mobile visual search. Then a conceptual model was built to verify the hypotheses that indicate the impact of mobile visual search on consumer perceived economic value and customer commitment, which further influence consumer's usage intention. Findings - The results show Convenience, Information quality, Personalization, Text-free search interface design and Visual communication of mobile visual search positively influence consumer perceived economic value and customer commitment and in turn positively affect consumer's usage intention. Moreover, the different levels of consumer online shopping orientation also found to have different effects on consumers' perception and behavior of using mobile visual search in online fashion shopping. Research implications or Originality - The present study verified that mobile visual search is a service tool that consumers want to use in the online fashion shopping journey since it provides economic benefits.

• The Korean Fashion and Textile Research Journal
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• 제17권5호
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• pp.731-740
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• 2015

Mobile (smartphone) search engine marketing is increasingly important. Accordingly, the development of visual apparel search technology to obtain easier and faster access to visual information in the apparel field is urgently needed. This study helps establish a proper classifying system for an apparel search after an analysis of search techniques for apparel search applications and existing domestic and overseas apparel sites. An annotation technique is developed in accordance with visual attributes and apparel categories based on collected data obtained by web crawling and apparel images collecting. The categorical composition of apparel is divided into wearing, image and style. The web evaluation site traces the correlations of the apparel category and apparel factors as dependent upon visual attributes. An appraisal team of 10 individuals evaluated 2860 pieces of merchandise images. Data analysis consisted of correlations between apparel, sleeve length and apparel category (based on an average analysis), and correlation between fastener and apparel category (based on an average analysis). The study results can be considered as an epoch-making mobile apparel search system that can contribute to enhancing consumer convenience since it enables an effective search of type, price, distributor, and apparel image by a mobile photographing of the wearing state.

• Journal of the Korean Society for information Management
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• 제29권1호
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• pp.175-190
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• 2012

This study aims to investigate the current status of mobile search functions of Korean search portals, namely Google Korea, Naver, Nate, Daum, and Yahoo Korea. This study focuses on unique mobile search functionalities, such as voice search, music search, code search, and visual/ object search. In particular, this study analyzed characteristics of these search functions and evaluated their performances based on the accuracy and the speed of recognition. The results of this study show that both Naver and Daum support various mobile searching functions, whereas Google only supports voice search. Nate and Yahoo do not offer any unique function. The results of this study can be applied to the portal's effective development of mobile search functionalities.

• Journal of Korea Multimedia Society
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• 제21권8호
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Journal of the Semiconductor & Display Technology
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• 제13권2호
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• pp.45-52
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• 2014

This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

• Annual Conference of KIPS
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.1422-1425
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• 2011

These days' mobile phones and their improved multimedia limits making it powerful enough to handle complicated tasks. Image processing related support for mobile devices is extremely comprehensive in mobile cyber museum. A key technical challenge is how to achieve the best-perceived image quality and transmitting data between client and server with given the limited screen size and display bit-depth of the mobile devices. This paper targets image processing features such as capturing rendering zooming, panning and image rotation for 360o view and customized algorithm related image processing with variety of search method i.e. alphabetical, visual search.

• Journal of KIISE
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• 제44권12호
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• pp.1313-1318
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• 2017

Aggregating local features in a single vector is a fundamental problem in an image search. In this process, the image search process can be speeded up if binary features which are extracted almost two order of magnitude faster than gradient-based features are utilized. However, in order to utilize the binary features in an image search, it is necessary to study the techniques for clustering binary features to generate binary visual words. This investigation is necessary because traditional clustering techniques for gradient-based features are not compatible with binary features. To this end, this paper studies the techniques for clustering binary features for the purpose of generating binary visual words. Through experiments, we analyze the trade-off between the accuracy and computational efficiency of an image search using binary features, and we then compare the proposed techniques. This research is expected to be applied to mobile applications, real-time applications, and web scale applications that require a fast image search.

• Electronics and Telecommunications Trends
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• 제29권1호
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• pp.61-71
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• 2014

모바일 비주얼 검색(MVS: Mobile Visual Search) 기술은 스마트폰 환경에서 질의 영상의 특징을 검출하고 그 주변 영역의 정보를 이용하여 추출한 서술자를 미리 구축된 영상정보 DB와 비교하여 검색하는 기술로 스마트폰의 보급과 네트워크 환경발달에 따라 응용서비스의 범위와 가능성이 확대되고 있다. 본 동향에서는 기존의 텍스트, 음성, QR코드 등의 검색을 넘어 인간이 보는 그대로를 검색하고자 하는 모바일 비주얼 검색의 기술 및 표준화 동향을 분석하고 향후 전망에 대해서 살펴보고자 한다.

• Journal of Information Processing Systems
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• 제6권1호
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• pp.33-42
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• 2010

GIS can only be applied to certain areas by storing format. It is subordinate to a system when displaying geographic information data. It is therefore inevitable for GIS to use GML that supports efficient usage of various geographic information data and interoperability for integration and sharing. The paper constructs VisualGML that translates currently-used geographic information such as DXF (Drawing Exchange Format), DWG (DraWinG), or SHP (Shapefile) into GML format for visualization. VisualGML constructs an integrated map pre-process module, which filters geographic information data according to its tag and properties, to provide the flexibility of a mobile device. VisualGML also provides two major GIS services for the user and administrator. It can enable visualizing location search. This is applied with a 3-Layer POI structure for the user. It has trace monitoring visualization through moving information of mobile devices for the administrator.

• Journal of information and communication convergence engineering
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• 제19권1호
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• pp.36-41
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• 2021

Text-based image retrieval is not only cumbersome as it requires the manual input of keywords by the user, but is also limited in the semantic approach of keywords. However, content-based image retrieval enables visual processing by a computer to solve the problems of text retrieval more fundamentally. Vision applications such as extraction and mapping of image characteristics, require the processing of a large amount of data in a mobile environment, rendering efficient power consumption difficult. Hence, an effective image retrieval method on mobile platforms is proposed herein. To provide the visual meaning of keywords to be inserted into images, the efficiency of image retrieval is improved by extracting keywords of exchangeable image file format metadata from images retrieved through a content-based similar image retrieval method and then adding automatic keywords to images captured on mobile devices. Additionally, users can manually add or modify keywords to the image metadata.