1,721,453 research outputs found
Player/Avatar Body Relations in Multimodal Augmented Reality Games
Full text linkAugmented reality research is finally moving towards multimodal experiences: more and more applications do not only include visuals, but also audio and even haptics. The purpose of multimodality in these applications can be to increase realism or to increase the amount or quality of communicated information. One particularly interesting and increasingly important application area is AR gaming, where the player can experience the virtual game integrated into the real environment and interact with it in a multimodal fashion. Currently, many games are set up such that the interaction is local (direct), however there are many cases in which remote (indirect) interaction will be useful or even necessary. In the latter case, the actions can be expressed through a virtual avatar, while the player's real body is also still perceivably present. The player then controls the motions and actions of the avatar, and receives multimodal feedback associated to the events occurring in the game. Can it be that the player starts to perceive the avatar as a (part of) him- or herself? Or does something even more intense take place? What are the benefits of this experience? The core of this research is to understand how multimodal perceptual configuration plays a role in the relation between a player and their in-game avatar
Digital Musicology and MIR: Papers, Projects and Challenges
No full textIn this paper we report on the ISMIR 2013 Demo and Late Breaking Session entitled Digital Musicology and MIR. Five papers were discussed as examples of interesting MIR contributions to musicology. Two important projects, Transforming Musicology and CompMusic, were briefly presented. Finally, this paper reports the first results of a questionnaire about challenges from Digital Musicology for MIR research. The most important outcomes are that lack of suitable musical data is still an important obstacle and that there is a great demand for tools and methods that make integrated access and analysis of symbolic and audio data possible
Proceedings of the 16th International Society for Music Information Retrieval Conference: October 26-30, 2015; Malaga, Spain
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On the Segmentation and Classification of Water in Videos
No full textThe automatic recognition of water entails a wide range of applications, yet little attention has been paid to solve this specific problem. Current literature generally treats the problem as a part of more general recognition tasks, such as material recognition and dynamic texture recognition, without distinctively analyzing and characterizing the visual properties of water. The algorithm presented here introduces a hybrid descriptor based on the joint spatial and temporal local behaviour of water surfaces in videos. The temporal behaviour is quantified based on temporal brightness signals of local patches, while the spatial behaviour is characterized by Local Binary Pattern histograms. Based on the hybrid descriptor, the probability of a small region of being water is calculated using a Decision Forest. Furthermore, binary Markov Random Fields are used to segment the image frames. Experimental results on a new and publicly available water database and a subset of the DynTex database show the effectiveness of the method for discriminating water from other dynamic and static surfaces and objects
Collecting annotations for induced musical emotion via online game with a purpose emotify
No full textOne of the major reasons why music is so enjoyable is its emotional impact. Indexing and searching by emotion would greatly increase the usability of online music collections. However, there is no consensus on the question which model of emotion would fit this task best. Such a model should be easy for listeners to use both to tag and to retrieve emotion, and should lead to unambiguous results. The latter is complicated not only due to linguistic issues, but also because musical emotion is a subjective phenomenon that depends on many extra-musical factors, such as mood of the listener, musical preferences, age, personality. We investigate this problem by creating a game with a purpose Emotify to collect emotional labels for a set of 400 musical excerpts in different genres. We use the Geneva Emotional Music Scales (GEMS) to annotate this corpus. In this technical report we analyze the data produced by the game. We find that the factors that influence induced musical emotion (in the order of decreasing importance) are musical preferences, mood and gender. We measure the agreement of listeners using Cronbach’s alpha and find that it differs hugely per emotional category (amazement, sadness and solemnity are most inconsistent, and tenderness, power and joyful activation - most consistent categories) and does not differ significantly among the four tested musical genres (rock, pop, classical and electronic music)
Novel Music Segmentation Interface and the Jazz Tune Collection
No full textIn this paper we present MOSSA, an easy-to-use interface for mobile devices, developed to annotate the segment structure of music. Moreover, we present the jazz tune collection (JTC), a database of 125 Jazz melodies annotated using MOSSA, and developed specifically for benchmarking of computational models of melody segmentation. Each melody in the JTC has been annotated with segment boundaries by three human listeners, and segment boundary salience by two human listeners. We provide a light analysis of the inter-annotation-agreement of the annotations in the JTC, and also test the likelihood of the annotations been made using ‘gap’ related cues (large pitch intervals or interonset-intervals) and ‘repetition’ related cues (exact/approximate repetition of the beginning or ending of phrases)
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