• ETRI Journal
• /
• v.43 no.4
• /
• pp.630-639
• /
• 2021

Autonomous driving requires a computerized perception of the environment for safety and machine-learning evaluation. Recognizing semantic information is difficult, as the objective is to instantly recognize and distinguish items in the environment. Training a model with real-time semantic capability and high reliability requires extensive and specialized datasets. However, generalized datasets are unavailable and are typically difficult to construct for specific tasks. Hence, a light detection and ranging semantic dataset suitable for semantic simultaneous localization and mapping and specialized for autonomous driving is proposed. This dataset is provided in a form that can be easily used by users familiar with existing two-dimensional image datasets, and it contains various weather and light conditions collected from a complex and diverse practical setting. An incremental and suggestive annotation routine is proposed to improve annotation efficiency. A model is trained to simultaneously predict segmentation labels and suggest class-representative frames. Experimental results demonstrate that the proposed algorithm yields a more efficient dataset than uniformly sampled datasets.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.392-412
• /
• 2018

Due to the semantic gap problem across different modalities, automatically retrieval from multimedia information still faces a main challenge. It is desirable to provide an effective joint model to bridge the gap and organize the relationships between them. In this work, we develop a deep image annotation and classification by fusing multi-modal semantic topics (DAC_mmst) model, which has the capacity for finding visual and non-visual topics by jointly modeling the image and loosely related text for deep image annotation while simultaneously learning and predicting the class label. More specifically, DAC_mmst depends on a non-parametric Bayesian model for estimating the best number of visual topics that can perfectly explain the image. To evaluate the effectiveness of our proposed algorithm, we collect a real-world dataset to conduct various experiments. The experimental results show our proposed DAC_mmst performs favorably in perplexity, image annotation and classification accuracy, comparing to several state-of-the-art methods.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.151-152
• /
• 2010

WWW images locate in structural, networking documents, so the importance of a word can be indicated by its location, frequency. There are two patterns for multi-cues ingegration annotation. The multi-cues integration algorithm shows initial promise as an indicator of semantic keyphrases of the web images. The latent semantic automatic keyphrase extraction that causes the improvement with the usage of multi-cues is expected to be preferable.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.2
• /
• pp.203-216
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.8C
• /
• pp.1133-1141
• /
• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.5
• /
• pp.11-18
• /
• 2008

One of important Issues in computer graphics field is to communicate among users in virtual world like secondlife. However, in 3D virtual world, users' needs to wish to build their own contents in 3D virtual space are rising, similarly, users produce own homepage and animation, and leave writing in notice board. In this paper, we tried to achieve this by introducing semantic annotation object concept, which is a kind of annotation method in 3D virtual world. User can retrieve an 3D object by searching corresponding annotation data. This method can build semantic 3D virtual world and enable users to search 3D objects by integrating 3D object and 2D semantic multimedia information. Also, through a comparison experiment with proposal system and general 3D virtual world. the performance of proposed system is evaluated.

• Journal of Korea Society of Industrial Information Systems
• /
• v.12 no.2
• /
• pp.49-59
• /
• 2007

This paper is about an system which can perform automatic semantic annotation to actualize "Semantic Web." Since it is impossible to tag numerous documents manually in the web, it is necessary to gather large Korean web documents as training data, and extract features by using natural language techniques and a thesaurus. After doing these, we constructed concept classifiers through the SVM (support vector machine) teaming algorithm. According to the characteristics of Korean language, morphological analysis and syntax analysis were used in this system to extract feature information. Based on these analyses, the concept code is mapped with Kadokawa thesaurus, which made it possible to map similar words and phrase to one concept code, to make training vectors. This contributed to rise the recall of our system. Results of the experiment show the system has a some possibility of semantic annotation.

• Electronics and Telecommunications Trends
• /
• v.25 no.2
• /
• pp.121-131
• /
• 2010

인터넷의 발전 과정에서 데이터 중심의 시맨틱 웹 기술과 서비스 중심의 웹서비스 기술은 시맨틱 웹서비스라는 융합기술로 발전하고 있다. 본 고에서는 시맨틱 웹서비스 실현의 핵심인 시맨틱 어노테이션(annotation) 기술을 소개하고, 접근 방식에 따라 톱다운 방식와 바텀업 방식으로 분류한 어노테이션 기술들을 비교 분석한다. 그리고 어노테이션 기술 중 WSMO 기반의 어노테이션을 이용하여 시맨틱 웹서비스를 모델링하는 사례를 보임으로써 시맨틱 웹서비스 실현의 가능성과 그 시기를 가늠해보고자 한다.

• Journal of Korea Multimedia Society
• /
• v.6 no.4
• /
• pp.565-575
• /
• 2003

This paper proposed context based annotation model and annotation ambiguity correction methods. The proposed model provides various annotation types, semantic models, and pen-based free drawing interface. Annotation correction method that is specifically based on the context which includes various textual and structure information between free-form marking and annotation. Also, interface for XML environment using the proposed model and correction methods is proposed and possibilities of application is looked at. The results from the implementation of the proposed method show that the annotated areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment

• Cross-Cultural Studies
• /
• v.52
• /
• pp.341-369
• /
• 2018

Li ShangYin (李商隱) was a poet who represented the late Tang period and authored more than 590 poems. In this paper, I have searched for various phonetic and semantic relationships through the attention of scholars' annotation about Li ShangYin (李商隱)'s poetry. As a result, we found 12 types of "examples that explain the phonetic and semantic relationships of poetic words" and five types of "examples that explain the features of poetic words and prosody." Especially, through analysis of "examples that explain the phonetic and semantic relationships of poetic words", it is divided into two types. The first type is that the scholars' annotation about Li ShangYin (李商隱)'s poetry and phonetic and semantic relationships of poetic words are matched, and the second type is that the scholars' annotation about Li ShangYin (李商隱)'s poetry and phonetic and semantic relationships of poetic words are inconsistent. In this study, I applied the theory of level and oblique tones for more detailed analysis of each type.