• Title/Summary/Keyword: Text Appearance Map

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Detection of Artificial Caption using Temporal and Spatial Information in Video (시·공간 정보를 이용한 동영상의 인공 캡션 검출)

  • Joo, SungIl;Weon, SunHee;Choi, HyungIl
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.2
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    • pp.115-126
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    • 2012
  • The artificial captions appearing in videos include information that relates to the videos. In order to obtain the information carried by captions, many methods for caption extraction from videos have been studied. Most traditional methods of detecting caption region have used one frame. However video include not only spatial information but also temporal information. So we propose a method of detection caption region using temporal and spatial information. First, we make improved Text-Appearance-Map and detect continuous candidate regions through matching between candidate-regions. Second, we detect disappearing captions using disappearance test in candidate regions. In case of captions disappear, the caption regions are decided by a merging process which use temporal and spatial information. Final, we decide final caption regions through ANNs using edge direction histograms for verification. Our proposed method was experienced on many kinds of captions with a variety of sizes, shapes, positions and the experiment result was evaluated through Recall and Precision.

Exploring Future Signals for Mobile Payment Services - A Case of Chinese Market - (모바일 결제 서비스에 대한 미래신호 예측 - 중국시장을 대상으로 -)

  • Bin Xuan;Seung Ik Baek
    • Journal of Service Research and Studies
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    • v.13 no.1
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    • pp.96-107
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    • 2023
  • The objective of this study is to explore future issues that Chinese users, who have the highest mobile payment service usage rate in the world, will be most interested in. For this purpose, after collecting text data from a Chinese SNS site, it classifies major keywords into 4 types of future signals by using Keyword Emergence Map (KEM) and Keyword Issue Map (KIM). Furthermore, to understand the four types of signals in detail, it performs the qualitative analysis on text related to each signal keyword. As a result, it finds that the strong signal, which is rapidly growing in keyword appearance frequency during this research period, includes the keywords related to the daily life of Chinese people, such as buses, subways, and household account books. Additionally, it find that the signal that appears frequently now, but with a low increase rate, includes various services that can replace cash payment, such as hongbao (cash payment) and bank cards. The weak signal and latent signal, which appear less often than other two signals, includes the keywords related to promotion events or changes in service regulations. Its result shows that the mobile payment services greatly have changed user's daily life beyond providing convenience. Furthermore, it shows that, in the Chinese market, in which card payment is not common, the mobile payment services have the great potential to completely replace cash payment.

Perception and Appraisal of Urban Park Users Using Text Mining of Google Maps Review - Cases of Seoul Forest, Boramae Park, Olympic Park - (구글맵리뷰 텍스트마이닝을 활용한 공원 이용자의 인식 및 평가 - 서울숲, 보라매공원, 올림픽공원을 대상으로 -)

  • Lee, Ju-Kyung;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.4
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    • pp.15-29
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    • 2021
  • The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.