• Journal of the Korea Society of Computer and Information
• /
• v.14 no.8
• /
• pp.51-58
• /
• 2009

In this paper. we propose search algorithm using Low Peak Feature of audio and image color value by which similar movies can be identified. Combing through entire video files for the purpose of recognizing and retrieving matching movies requires much time and memory space. Moreover, these methods still share a critical problem of erroneously recognizing as being different matching videos that have been altered only in resolution or converted merely with a different codec. Thus we present here a similar-video-retrieval method that relies on analysis of audio patterns, whose peak features are not greatly affected by changes in the resolution or codec used and image color values. which are used for similarity comparison. The method showed a 97.7% search success rate, given a set of 2,000 video files whose audio-bit-rate had been altered or were purposefully written in a different codec.

• Journal of KIISE:Databases
• /
• v.30 no.5
• /
• pp.494-506
• /
• 2003

Recently, explosive popularity of multimedia information has triggered the need for retrieving multimedia contents efficiently from the database including audio, video and images. In this paper, we propose an XML-based retrieval scheme and a data model that complement the weak aspects of annotation and conent based retrieval methods. The Property and hierarchy structure of image and video data are represented and manipulated based on the Multimedia Description Schema (MDS) that conforms to the MPEG-7 standard. For audio contents, pitch contours extracted from their acoustic features are converted into UDR string. Especially, to improve the retrieval performance, user's access pattern and frequency are utilized in the construction of an index. We have implemented a prototype system and evaluated its performance through various experiments.

• Journal of Korea Society of Industrial Information Systems
• /
• v.11 no.3
• /
• pp.10-14
• /
• 2006

To effectively manage a very large amount of music data, we need an indexing technique based on audio features. But the indexing techniques for audiofeatures have not been studied completely. In this paper, we describe a content-based music information retrieval technique for audio features using the TIP-indexing file. In addition, we develop and experiment the TIP-indexing files using various blocking factors to present performance comparisons for effective indexing. Experimental results show the effectiveness of the proposed techniques.

• Journal of Korea Society of Industrial Information Systems
• /
• v.11 no.5
• /
• pp.18-27
• /
• 2006

Rapid increase of the amount of music data demands for a new method that allows efficient similarity retrieval of music genre using audio features in music databases. To build this similarity retrieval, an indexing techniques that support audio features as a time-series pattern and data mining technologies are needed. In this paper, we address the development of a system that retrieves similar genre music based on the indexing techniques. We first propose the structure of content-based music genre retrieval system based on the time-series pattern index file and data mining technologies. In addition, we implement the time-series pattern index file using audio features and present performance analysis of the time-series pattern index file for similar genre retrieval. The experiments are performed on real data to verify the performance of the proposed method.

• ETRI Journal
• /
• v.28 no.4
• /
• pp.509-512
• /
• 2006

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.

• Journal of Broadcast Engineering
• /
• v.9 no.1
• /
• pp.2-7
• /
• 2004

In this paper, we proposed the content-based music information retrieval technique using some MPEG-7 low-level descriptors. Especially, pitch information and timbral features can be applied in music genre classification, music retrieval, or QBH(Query By Humming) because these can be modeling the stochasticpattern or timbral information of music signal. In this work, we restricted the music domain as O.S.T of movie or soap opera to apply broadcasting system. That is, the user can retrievalthe information of the unknown music using only an audio clip with a few seconds extracted from video content when background music sound greeted user's ear. We proposed the audio feature set organized by MPEG-7 descriptors and distance function by vector distance or ratio computation. Thus, we observed that the feature set organized by pitch information is superior to timbral spectral feature set and IFCR(Intra-Feature Component Ratio) is better than ED(Euclidean Distance) as a vector distance function. To evaluate music recognition, k-NN is used as a classifier

• The KIPS Transactions:PartB
• /
• v.17B no.2
• /
• pp.99-106
• /
• 2010

In this paper, we propose the construction of multi-queries and consistency principle for the user's emotion-based music retrieval system. The features used in the system are MPEG-7 audio descriptors, which are international standards recommended for content-based audio retrievals. In addition we propose the method to determine the weight that represent the importance of each descriptor for each emotion in order to reduce the computation. Also, the proposed retrieval algorithm that uses the relevance feedback based on consistency principal and multi-queries improves the success ratio of musics corresponding to user's emotion.

• Journal of the Korea Society of Computer and Information
• /
• v.3 no.4
• /
• pp.10-18
• /
• 1998

Video information is an important component of multimedia system such as Digital Library. World-Wide Web(WWW) and Video-On-Demand(VOD) service system. It can support various types of information because of including audio-visual, spatial-temporal and semantics information. In addition, it requires the ability of retrieving the specific scene of video instead of entire retrieval of video document. Therefore, so as to support a variety of retrieval, this paper models metadata using video document structure information that consists of hierarchical structure, and designs database schema that can manipulate video document.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.2
• /
• pp.461-468
• /
• 2000

Amounts of audio data used in several computer application have necessitated the development of audio database systems with newer features such as content-based queries and similarity searches to manage and use such data. Fast and accurate retrievals for content-based queries are crucial for such systems to be useful. Efficient content-based indexing and similarity searching schemes are keys to providing fast and relevant data retrievals. This paper present a method for indexing of Korean Traditional Music audio data based on wavelets. Also this paper present possibility of wavelet based audio indexing.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.12
• /
• pp.224-231
• /
• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).