Showing papers on "Multimedia database published in 2015"

Multimedia mining research - an overview

Abstract: Multimedia data mining is a popular research domain which helps to extract interesting knowledge from multimedia data sets such as audio, video, images, graphics, speech, text and combination of several types of data sets. Normally, multimedia data are categorized into unstructured and semi-structured data. These data are stored in multimedia databases and multimedia mining is used to find useful information from large multimedia database system by using various multimedia techniques and powerful tools. This paper provides the basic concepts of multimedia mining and its essential characteristics. Multimedia mining architectures for structured and unstructured data, research issues in multimedia mining, data mining models used for multimedia mining and applications are also discussed in this paper. It helps the researchers to get the knowledge about how to do their research in the field of multimedia mining.

Sparse structure regularized ranking

Abstract: Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

Intelligent user-defined consulting platform generating system

Abstract: The invention provides an intelligent user-defined consulting platform generating system. The generating system comprises a three-dimensional digital human modeling unit, a storage unit, a Chinese question and answer engine unit, a Chinese question and answer background denoising unit, a virtual human driving engine, a virtual human displaying unit, a multimedia database, a digital multimedia displaying unit, a multimedia database management unit, a multimedia database management subunit, a cloud database unit, a long-distance client side and the like. The system is wide in application range, easy to operate and high in experience performance as an interface of touch type human-computer interaction is user-friendly.

Query by Shape for Image Retrieval from Multimedia Databases

Abstract: Efficient methods of image retrieval is one of the most important challenges in the scope of the management of large multimedia databases. Existing methods for querying, based on a textual description e.g. keywords or based on image content, are not sufficient for the most applications. Methods based on semantic features are more suitable. In this paper we propose a new query by shape (QS) method for image retrieval from multimedia databases. Each image in the database is represented as a set of graphical objects, which are specified using graphical primitives like lines, circles, polygons etc. To retrieve images containing the given object, the object shape should be provided. Next, the efficient algorithm for testing the similarity of shapes is applied. The preliminary results showed the high effectiveness of the QS method.

The scalable distributed two-layer Content Based Image Retrieval data store

Abstract: The multimedia databases are becoming more and more popular nowadays. One of their main problem is a huge data amount storage. Another problem with multimedia databases is querying. Traditional approaches, based on textual keywords are not sufficient. More advanced techniques, incorporating image content features, should be used. In this paper we propose new multimedia database structure with ability of Content Based Image Retrieval which is based on our previous work: Query by Shape method (QS). Query by Shape is a method which is based on decomposing an object into features. Each feature may consists of shape primitive, a color or a texture. In this paper we only use shape primitives. In order to achieve high scalability and workload control, we propose a modified Scalable Distributed Two-layer Data Structure, as a storage. The modification incorporates adding tree structure, comparing algorithm and returning a set of results to the client.

MLES: Multilayer Exploration Structure for Multimedia Exploration

Abstract: The traditional content-based retrieval approaches usually use flat querying, where whole multimedia database is searched for a result of some similarity query with a user specified query object. However, there are retrieval scenarios (e.g., multimedia exploration), where users may not have a clear search intents in their minds, they just want to inspect a content of the multimedia collection. In such scenarios, flat querying is not suitable for the first phases of browsing, because it retrieves the most similar objects and does not consider a view on part of a multimedia space from different perspectives. Therefore, we defined a new Multilayer Exploration Structure (MLES), that enables exploration of a multimedia collection in different levels of details. Using the MLES, we formally defined popular exploration operations (zoom-in/out, pan) to enable horizontal and vertical browsing in explored space and we discussed several problems related to the area of multimedia exploration.

Gradient-based Signatures for Efficient Similarity Search in Large-scale Multimedia Databases

Abstract: With the continuous rise of multimedia, the question of how to access large-scale multimedia databases efficiently has become of crucial importance. Given a multimedia database comprising millions of multimedia objects, how to approximate the content-based properties of the corresponding feature representations in order to carry out similarity search efficiently and with high accuracy? In this paper, we propose the concept of gradient-based signatures in order to aggregate content-based features of multimedia objects by means of generative models. We provide theoretical insights into our approach including closed-form expressions for the computation of gradient-based signatures with respect to Gaussian mixture models and additionally investigate different binarization methods for gradient-based signatures in order to query databases comprising millions of multimedia objects with high accuracy in less than one second.

Data synchronization method of PC (Personnel Computer) end and mobile terminal based on hydraulic polling business

Abstract: The invention discloses a data synchronization method of a PC (Personnel Computer) end and a mobile terminal based on hydraulic polling business. The data synchronization method mainly comprises two parts of uploading polling data at the mobile terminal and downloading the polling data at the PC end, wherein uploading the polling data at the mobile terminal comprises the following steps of importing polling attribute basic information and multimedia data information in mobile equipment into the PC end, converting the basic data information into data objects through sorting operation of the polling data, storing the data objects in a database and storing multimedia data in a multimedia database to effectively manage the polling data; downloading the polling data at the PC end comprises the following steps of downloading newest hydraulic polling data to the mobile terminal from the PC end to facilitate obtaining result information of last polling when a user carries out polling at each time, and comparing with the current polling site condition to judge the hydraulic safety situation. According to the data synchronization method, the polling data can be automatically, timely and accurately put in storage conveniently, the processing time for the polling data is reduced, and the working efficiency and the accuracy for polling personnel can be improved.

Nearest multi-prototype based music mood classification

Abstract: Music mood classification is a crucial component in the field of multimedia database retrieval and computational musicology. There is a constantly growing interest in developing and evaluating music information retrieval (MIR) systems that can provide automated access to the music mood. The proposed method considers the different types of audio features. From each feature's frame, a bin histogram has been calculated to preserve all important information associated with it. The histogram bins of each feature are used to calculate the similarity matrix, and the number of similarity matrices depends on the number of audio features. Therefore, there are 59 similarity matrixes from the corresponding same amount of audio features. The intra and inter similarity matrix are used to calculate the intra-inter similarity ratio. These similarity ratios are sorted in descending order in each feature. Among them, some of the selected similarity ratios are ultimately used as prototypes from each feature and are used for classification by designing the nearest multi-prototype classifier. The Coimbra mood dataset is used to measure the overall performance of the proposed method. We achieved competitive classification accuracies as compared with other existing state-of-the-art music mood classification techniques.

Mexican archaeological image retrieval based on object matching and a local descriptor

Abstract: Content-based image retrieval (CBIR) is a hard task which consists in retrieving similar content from a large multimedia database. In the literature, in order to extract descriptors from the images the CBIR techniques use several low-level features such as color, texture, shape, contours, among others. In the recent years, several local descriptors based on the detection of feature points have been used to retrieve the most similar images with different geometric and photometric characteristics. In this paper we propose a CBIR technique that involves the combination of a local descriptor obtained from the Speeded Up Robust Feature (SURF) algorithm together with an effective and fast object matching operation in order to improve the search speed and the retrieval accuracy related to the Mexican archaeological imaging. In order to reduce the computational complexity of the proposed method, Quarter Common Intermediate Format (QCIF) is used previous of computing the SURF descriptor. To measure the performance of the proposed technique the precision and recall metrics are used. The experimental results show the accuracy of the proposed CBIR technique applied to a data base of Mexican culture images that are captured by several environmental conditions and different acquisition equipment.

Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study

Abstract: The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multifaceted retrieval is opposed to the potential complexity of data setup procedures and development of multimedia annotations. Additionally, a recent study has shown that databases of emotionally annotated multimedia are still being predominately searched manually which highlights the need to study this retrieval modality. To this regard we present a study with N = 75 participants aimed to evaluate the influence of keywords and dimensional emotions in manual retrieval of pictures. The study showed that if the multimedia database is comparatively small emotional annotations are sufficient to achieve a fast retrieval despite comparatively lesser overall accuracy. In a larger dataset semantic annotations became necessary for efficient retrieval although they contributed to a slower beginning of the search process. The experiment was performed in a controlled environment with a team of psychology experts. The results were statistically consistent with validates measures of the participants' perceptual speed.

Automatic Mapping Magnetic Resonance Images into Multimedia Database Using SIFT

Abstract: This paper focuses on the representation of magnetic resonances of different parts of the human body, such as knees, spinal column, arms, elbows, etc., using ontologies. First, it maps the resonance images in a multimedia database. Then, automatically, using the SIFT pattern recognition algorithm, descriptors of the images stored in the database are extracted in order to recover useful data for the user; it uses the ontologies as an artificial intelligence tool and, in consequence, reduces generation of useless data. Why do we think this is an interesting task? Because, if the user requires information about any topics or (s)he has some illness or needs to undergo magnetic resonance, this tool will show him/her images and text to convey a better understanding, helping to obtain useful conclusions. Artificial intelligence techniques are used, such as machine learning, knowledge representation, and pattern recognition. The ontological relations introduced here are based on the common representation of language, using definition dictionaries, Roget's thesaurus, synonym dictionaries, and other resources The system generates an output in the OM ontological language [1]. This language represents a structure where our system adds the data scanned by the SIFT algorithm. The tests have been made in Spanish; however, thanks to the portability of our system, it is possible to extend the method to any language.

Query acceleration in multimedia database systems

Abstract: -With the increasing popularity of the World Wide Web comes the enormous increase in stored digital contents, which could challenge users to search and use the multimedia data efficiently. This work focuses on hastening techniques for efficient retrieval of multimedia data. In this paper, we exploit the use of bit-vectors to accelerate queries in multimedia databases. We use a compressed bit-vector to minimize the amount of data cashed on disk; thus, reducing the amount of memory and time needed to execute queries. We also compare our scheme with other related strategies. Keywords-multimedia; bit vectors; query accelerations.

Towards a computational processing of oral dialectal data

Abstract: In this paper, we discuss issues concerning the computational processing of oral data in a unified framework for the exploitation of oral and written dialectal corpora. We describe the analysis and design of a multimedia database and software for storing and retrieving dialectal data, focusing on the subsystem of oral resources from three Greek dialects in Asia Minor. We discuss problems concerning the archiving and exploitation of such an oral corpus and we propose solutions.

Hydropower station water conservancy project inspection system supporting multi-terminal platform

Abstract: The invention discloses a hydropower station water conservancy project inspection system capable of supporting a multi-terminal platform An operating method of the system comprises the following steps that mobile equipment synchronizes historical data; the mobile equipment acquires water conservancy project inspection data; the mobile equipment uploads latest inspection data and a PC terminal manages the inspection data and automatically generates a report The mobile equipment downloads the latest water conservancy project inspection data to a mobile terminal from the PC terminal, result information of the last inspection is conveniently acquired by a user during inspection in each time, and the information can be compared with current inspection site condition The water conservancy project inspection field data are recorded by using a mobile terminal The water conservancy project inspection data information in the mobile equipment is introduced into the PC terminal, basic data information can be converted into a data object by virtue of classified processing of the inspection data and is stored into a database, the multimedia data are stored into a multimedia database, and the inspection data can be effectively managed The PC terminal manages the inspection data and automatically generates the report, and the latest uploaded data are displayed in a report form According to the system disclosed by the invention, the working efficiency and accuracy of inspectors are improved

Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study

Abstract: The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multifaceted retrieval is opposed to the potential complexity of data setup procedures and development of multimedia annotations. Additionally, a recent study has shown that databases of emotionally annotated multimedia are still being predominately searched manually which highlights the need to study this retrieval modality. To this regard we present a study with N = 75 participants aimed to evaluate the influence of keywords and dimensional emotions in manual retrieval of pictures. The study showed that if the multimedia database is comparatively small emotional annotations are sufficient to achieve a fast retrieval despite comparatively lesser overall accuracy. In a larger dataset semantic annotations became necessary for efficient retrieval although they contributed to a slower beginning of the search process. The experiment was performed in a controlled environment with a team of psychology experts. The results were statistically consistent with validates measures of the participants' perceptual speed.

Method, system and platform for the creation and operation of a multimedia database

Abstract: The invention relates to a method, system and platform for the creation and operation of databases in order to allow searches for relevant multimedia data and images.

Technology review on managing and mining web multimedia database

Abstract: The huge amount of unstructured data available on the web and the multimedia manages and storage technologies have led to incredible growth in very large and detailed multimedia database. Multimedia mining has proved to be a successful approach for extracting hidden knowledge from huge collections of structured digital data stored in databases. Also it is an inter disciplinary endeavor that draws upon expertise in multimedia retrieval, classification and data mining. Managing and mining web multimedia database is a framework that manages different types of data potentially represented in a wide diversity of formats on a wide array of media sources. It provides support for multimedia data types, and facilitate for creation, storage, access, managing and control of a multimedia database. The purpose of this paper is to provide overview of multimedia mining, categorizing the web multimedia database with various data mining techniques. This article also represents the important concepts of the multimedia databases on the web and how these databases have to managed and mined to extract patterns and trends.