Fraunhofer Institute for Digital Media Technology

Germany

Fraunhofer Institute for Digital Media Technology

Germany

Time filter

Source Type

Nowak S.,Fraunhofer Institute for Digital Media Technology | Ruger S.,Open University Milton Keynes
MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval | Year: 2010

The creation of golden standard datasets is a costly business. Optimally more than one judgment per document is obtained to ensure a high quality on annotations. In this context, we explore how much annotations from experts differ from each other, how different sets of annotations influence the ranking of systems and if these annotations can be obtained with a crowdsourcing approach. This study is applied to annotations of images with multiple concepts. A subset of the images employed in the latest ImageCLEF Photo Annotation competition was manually annotated by expert annotators and non-experts with Mechanical Turk. The inter-annotator agreement is computed at an image-based and concept-based level using majority vote, accuracy and kappa statistics. Further, the Kendall and Kolmogorov-Smirnov correlation test is used to compare the ranking of systems regarding different ground-truths and different evaluation measures in a benchmark scenario. Results show that while the agreement between experts and non-experts varies depending on the measure used, its influence on the ranked lists of the systems is rather small. To sum up, the majority vote applied to generate one annotation set out of several opinions, is able to filter noisy judgments of non-experts to some extent. The resulting annotation set is of comparable quality to the annotations of experts. Copyright 2010 ACM.


Saul C.,Fraunhofer Institute for Digital Media Technology | Wuttke H.-D.,TU Ilmenau
Proceedings of the 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012 | Year: 2012

Over the last decade, a large number of e-assessment system and tools were developed. No matter whether they are stand-alone or integrated into learning management systems, they all have two things in common: (1) they do not consider individual aspects and (2) they do not require/encourage students to actively thinking, problem-solving, etc. The work presented in this paper focuses on the second aspect and provides a generic model that enables integrating Interactive Content Objects (ICOs) with established e-assessment systems and specifies the interactions with these objects. ICOs is the generic term for interactive tools, which do not restrict students to be passive recipients, but also engage them with material that is responsive to their actions. This results in more objective assessment findings and deeper learning, because students can learn from mistakes and make sense from unexpected situations. © 2012 IEEE.


Jantke K.P.,Fraunhofer Institute for Digital Media Technology
CSEDU 2010 - 2nd International Conference on Computer Supported Education, Proceedings | Year: 2010

Playful learning is an old dream of mankind since Comenius' early work on didactics (Comenius, 1628). But playful learning should not be oversimplified and thoughtlessly identified with effortless fun. In contrast, playful learning may be some fun, although being demanding requiring concentration, devotion and stamina. Gorge is the name of a digital game designed for the purpose of developing certain technology competence. It is in use with students of an age ranging from about 12 to 24. This poster surveys the concepts and the game.


Nowak S.,Fraunhofer Institute for Digital Media Technology
Proceedings - International Conference on Pattern Recognition | Year: 2010

The Photo Annotation Task is performed as one task in the ImageCLEF@ICPR contest and poses the challenge to annotate 53 visual concepts in Flickr photos. Altogether 12 research teams met the multilabel classification challenge and submitted solutions. The participants were provided with a training and a validation set consisting of 5,000 and 3,000 annotated images, respectively. The test was performed on 10,000 images. Two evaluation paradigms have been applied, the evaluation per concept and the evaluation per example. The evaluation per concept was performed by calculating the Equal Error Rate and the Area Under Curve (AUC). The evaluation per example utilizes a recently proposed Ontology Score. For the concepts, an average AUC of 86.5% could be achieved, including concepts with an AUC of 96%. The classification performance for each image ranged between 59% and 100% with an average score of 85%. © 2010 IEEE.


Franck A.,Fraunhofer Institute for Digital Media Technology
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics | Year: 2011

Arbitrary sample rate conversion (ASRC) is used in many applications of DSP. ASRC algorithms based on integer-ratio oversampling and continuous-time resampling filters enable good resampling quality for wideband signals. © 2011 IEEE.


Jantke K.P.,Fraunhofer Institute for Digital Media Technology
Communications in Computer and Information Science | Year: 2013

Memetics and meme media technologies deployed for some purpose of technology enhanced learning need a certain systematization. Didactic principles, patterns of didactically driven activities, and the like may be seen as memes. Those memes are encapsulated as meme media occurring in digital representations of anticipated learning experiences named storyboards. Digital storyboarding is the preferred technology of designing anticipated learning experiences based on didactic knowledge. Encapsulated didactic memes-knowledge, principles, artifices, use cases-occur in digital storyboards and, through using, changing and re-using, may be subject to inheritance, mutation, cross-over and natural selection. © Springer-Verlag Berlin Heidelberg 2013.


Dressler K.,Fraunhofer Institute for Digital Media Technology
Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011 | Year: 2011

This paper proposes an efficient approach for the identification of the predominant voice from polyphonic musical audio. The algorithm implements an auditory streaming model which builds upon tone objects and salient pitches. The formation of voices is based on the regular update of the frequency and the magnitude of so called streaming agents, which aim at salient tones or pitches close to their preferred frequency range. Streaming agents which succeed to assemble a big magnitude start new voice objects, which in turn add adequate tones. The algorithm was evaluated as part of a melody extraction system during the MIREX audio melody extraction evaluation, where it gained very good results in the voicing detection and overall accuracy. © 2011 International Society for Music Information Retrieval.


Jantke K.P.,Fraunhofer Institute for Digital Media Technology
Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing, PIC 2010 | Year: 2010

Learning by playing is a rather old dream coming next after learning when sleeping; at least, it is ambitious. Some authors report an enormous success of game-based learning, whereas others speak about a caricature of computer games and a reactionary use of learning theory. Opinions are quite divided. It seems difficult to resolve contradictions and to settle a dispute as long as there is no appropriate terminology available. There is an apparent need of some taxonomy for a digital games science. This paper contributes to a taxonomy of digital games, in general, and to taxonomic concepts of game-based learning, in particular. Taxonomic concepts such as extra game play and meta game play prove successful for the understanding of game playing impact as well as for guiding serious games design. ©2010 IEEE.


Dressler K.,Fraunhofer Institute for Digital Media Technology
Proceedings of the 9th International Conference on Digital Audio Effects, DAFx 2006 | Year: 2013

This paper provides a detailed description of the spectral analysis front-end of a melody extraction algorithm. Our particular approach aims at extracting the sinusoidal components from the audio signal. It includes a novel technique for the efficient computation of STFT spectra in different time-frequency resolutions. Furthermore, we exploit the application of local sinusoidality criteria, in order to detect stable sinusoids in individual FFT frames. The evaluation results show that a multi resolution analysis improves the sinusoidal extraction in polyphonic audio.


Rennies J.,Fraunhofer Institute for Digital Media Technology
Proceedings of Meetings on Acoustics | Year: 2013

The calculation of perceived loudness is an important factor in many applications such as the assessment of noise emissions. Generally, loudness of stationary sounds can be accurately predicted by existing models. For sounds with time-varying characteristics, however, there are still discrepancies between experimental data and model predictions, even with the most recent loudness models. This contribution presents a series of experiments in which loudness was measured in normal-hearing subjects with different types of realistic signals using an adaptive loudness matching procedure and categorical loudness scaling. The results of both methods indicate that loudness of speech-like signals is largely determined by the long-term spectrum, while other speech-related properties (particularly temporal modulations) play only a minor role. Loudness of speech appears to be quite robust towards even severe signal modifications, as long as the long-term spectrum is similar. In contrast, loudness of technical, strongly impulsive signals is considerably influenced by temporal modulations. For some of the signals, loudness could not be predicted by current models. Since the perceived loudness was underestimated by the models for some signals, but overestimated for other signals, a simple adjustment of the employed time constants in the temporal integration stage could not eliminate the discrepancies. © 2013 Acoustical Society of America.

Loading Fraunhofer Institute for Digital Media Technology collaborators
Loading Fraunhofer Institute for Digital Media Technology collaborators