Petra Budíková

Petra Budíková
Masaryk University | MUNI · Faculty of Informatics

Ph.D.

About

22
Publications
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161
Citations

Publications

Publications (22)
Conference Paper
Full-text available
For complex data types such as multimedia, traditional data management methods are not suitable. Instead of attribute matching approaches, access methods based on object similarity are becoming popular. Recently, this resulted in an intensive research of indexing and searching methods for the similarity-based retrieval. Nowadays, many efficient met...
Article
Full-text available
Multimedia information is becoming an ubiquitous part of our lives, which brings an equally ubiquitous need for efficient multimedia retrieval. One of the possible solutions to this problem is to attach text descriptions to multimedia data objects, thus allowing users to utilize traditional text search mechanisms. Search-based annotation techniques...
Chapter
There is a growing amount of human motion data captured as a continuous 3D skeleton sequence without any information about its semantic partitioning. To make such unsegmented and unlabeled data efficiently accessible, we propose to transform them into a text-like representation and employ well-known text retrieval models. Specifically, we partition...
Article
Full-text available
Digitization of human motion using skeleton representations offers exciting possibilities for a large number of applications but, at the same time, requires innovative techniques for their effective and efficient processing. Content-based processing of skeleton data has developed rapidly in recent years, focusing mainly on specialized prototypes wi...
Article
With the increasing availability of human motion data captured in the form of 2D or 3D skeleton sequences, more complex motion recordings need to be processed. In this paper, we focus on similarity-based indexing and efficient retrieval of motion episodes — medium-sized skeleton sequences that consist of multiple semantic actions and correspond to...
Chapter
Large-scale data management and retrieval in complex domains such as images, videos, or biometrical data remains one of the most important and challenging information processing tasks. Even after two decades of intensive research, many questions still remain to be answered before working tools become available for everyday use. In this work, we foc...
Article
The rapid growth of unstructured data, commonly denoted as the Big Data challenge, requires new technologies that are capable of dealing with complex data objects such as multimedia. In this work, the authors focus on the content-based retrieval approach, which is able to organize such data by exploiting the similarity of data content. In particula...
Conference Paper
Full-text available
The importance of automatic image annotation as a tool for handling large amounts of image data has been recognized for several decades. However, working tools have long been limited to narrow-domain problems with a few target classes for which precise models could be trained. With the advance of similarity searching, it now becomes possible to emp...
Article
Full-text available
In spite of the development of content-based data management, text-based searching remains the primary means of multimedia retrieval in many areas. Automatic creation of text metadata is thus a crucial tool for increasing the findability of multimedia objects. Search-based annotation tools try to provide content-descriptive keywords by exploiting w...
Article
Full-text available
This paper constitutes an extension to the report on DISA-MU team participation in the ImageCLEF 2014 Scalable Concept Image Annotation Task as published in [3]. Specifically, we introduce a new similarity search component that was implemented into the system, report on the results achieved by utilizing this component, and analyze the influence of...
Conference Paper
Full-text available
This paper presents an annotation tool developed by the DISA Laboratory for the ImageCLEF 2014 Scalable Concept Image An-notation challenge. Our solution exploits the search-based annotation paradigm and utilizes several sources of semantic information to deter-mine the relevance of candidate concepts. Rather than relying on the quality of training...
Conference Paper
Full-text available
Effective management of multimedia data is becoming vital for success in the modern era of omnipresent data. Summarization tools, which allow users to quickly get the gist of a given data collection and have proven their usefulness in text domain, are now gaining popularity also in multimedia processing. However, existing algorithms provide visual-...
Conference Paper
Full-text available
Unprecedented amounts of digital data are becoming available nowadays, but frequently the data lack some semantic information necessary to effectively organize these resources. For images in particular, textual annotations that represent the semantics are highly desirable. Only a small percentage of images is created with reliable annotations, ther...
Conference Paper
Full-text available
In all subfields of information retrieval, test datasets and ground truth data are important tools for testing and comparison of new search methods. This is also reflected by the image retrieval community where several benchmarking activities have been created in past years. However, the number of available test collections is still rather small an...
Conference Paper
Full-text available
Current multimedia search technology is, especially in commercial applications, heavily based on text annotations. However, there are many applications such as image hosting web sites (e.g. Flickr or Picasa) where the text metadata are of poor quality in general. Searching such collections only by text gives usually rather unsatisfactory results. O...
Conference Paper
Full-text available
With the rapid growth of multimedia data, a lot of attention has been recently devoted to the development of multimedia retrieval systems. The research has followed two main directions: The first one applies existing text-search mechanisms to retrieve multimedia data based on its descriptive annotations, the second approach retrieves data by conten...
Conference Paper
Full-text available
The Content-based Photo Image Retrieval (CoPhIR) dataset is the largest available database of digital images with corresponding visual descriptors. It contains five MPEG-7 global descriptors extracted from more than 106 million images from Flickr photo-sharing system. In this paper, we analyze this dataset focusing on 1) efficiency of similarity-ba...
Conference Paper
Full-text available
Current information systems are required to process complex digital objects, which are typically characterized by multiple descriptors. Since the values of many descriptors belong to non-sortable domains, they are effectively comparable only by a sort of similarity. Moreover, the scalability is very important in the current digital-explosion age. T...

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