Streaming and User Behaviour in Omnidirectional Videos

Omnidirectional videos (ODVs) have gone beyond the passive paradigm of traditional video, offering higher degrees of immersion and interaction. The revolutionary novelty of this technology is the possibility for users to interact with the surrounding environment, and to feel a sense of engagement and presence in a virtual space. Users are clearly the main driving force of immersive applications and consequentially the services need to be properly tailored to them. In this context, this chapter highlights the importance of the new role of users in ODV streaming applications, and thus the need for understanding their behaviour while navigating within ODVs. A comprehensive overview of the research efforts aimed at advancing ODV streaming systems is also presented. In particular, the state-of-the-art solutions under examination in this chapter are distinguished in terms of system-centric and user-centric streaming approaches: the former approach comes from a quite straightforward extension of well-established solutions for the 2D video pipeline while the latter one takes the benefit of understanding users’ behaviour and enable more personalised ODV streaming

Cultural Heritage Storytelling, Engagement and Management in the Era of Big Data and the Semantic Web

The current Special Issue launched with the aim of further enlightening important CH areas, inviting researchers to submit original/featured multidisciplinary research works related to heritage crowdsourcing, documentation, management, authoring, storytelling, and dissemination. Audience engagement is considered very important at both sites of the CH production–consumption chain (i.e., push and pull ends). At the same time, sustainability factors are placed at the center of the envisioned analysis. A total of eleven (11) contributions were finally published within this Special Issue, enlightening various aspects of contemporary heritage strategies placed in today’s ubiquitous society. The finally published papers are related but not limited to the following multidisciplinary topics:Digital storytelling for cultural heritage;Audience engagement in cultural heritage;Sustainability impact indicators of cultural heritage;Cultural heritage digitization, organization, and management;Collaborative cultural heritage archiving, dissemination, and management;Cultural heritage communication and education for sustainable development;Semantic services of cultural heritage;Big data of cultural heritage;Smart systems for Historical cities – smart cities;Smart systems for cultural heritage sustainability

Analysis of user behavior with different interfaces in 360-degree videos and virtual reality

[eng] Virtual reality and its related technologies are being used for many kinds of content, like virtual environments or 360-degree videos. Omnidirectional, interactive, multimedia is consumed with a variety of devices, such as computers, mobile devices, or specialized virtual reality gear. Studies on user behavior with computer interfaces are an important part of the research in human-computer interaction, used in, e.g., studies on usability, user experience or the improvement of streaming techniques. User behavior in these environments has drawn the attention of the field but little attention has been paid to compare the behavior between different devices to reproduce virtual environments or 360-degree videos. We introduce an interactive system that we used to create and reproduce virtual reality environments and experiences based on 360-degree videos, which is able to automatically collect the users’ behavior, so we can analyze it. We studied the behavior collected in the reproduction of a virtual reality environment with this system and we found significant differences in the behavior between users of an interface based on the Oculus Rift and another based on a mobile VR headset similar to the Google Cardboard: different time between interactions, likely due to the need to perform a gesture in the first interface; differences in spatial exploration, as users of the first interface chose a particular area of the environment to stay; and differences in the orientation of their heads, as Oculus users tended to look towards physical objects in the experiment setup and mobile users seemed to be influenced by the initial values of orientation of their browsers. A second study was performed with data collected with this system, which was used to play a hypervideo production made of 360-degree videos, where we compared the users’ behavior with four interfaces (two based on immersive devices and the other two based on non-immersive devices) and with two categories of videos: we found significant differences in the spatiotemporal exploration, the dispersion of the orientation of the users, in the movement of these orientations and in the clustering of their trajectories, especially between different video types but also between devices, as we found that in some cases, behavior with immersive devices was similar due to similar constraints in the interface, which are not present in non-immersive devices, such as a computer mouse or the touchscreen of a smartphone. Finally, we report a model based on a recurrent neural network that is able to classify these reproductions with 360-degree videos into their corresponding video type and interface with an accuracy of more than 90% with only four seconds worth of orientation data; another deep learning model was implemented to predict orientations up to two seconds in the future from the last seconds of orientation, whose results were improved by up to 19% by a comparable model that leverages the video type and the device used to play it.[cat] La realitat virtual i les tecnologies que hi estan relacionades es fan servir per a molts tipus de continguts, com entorns virtuals o vídeos en 360 graus. Continguts multimèdia omnidireccional i interactiva són consumits amb diversos dispositius, com ordinadors, dispositius mòbils o aparells especialitzats de realitat virtual. Els estudis del comportament dels usuaris amb interfícies d’ordinador són una part important de la recerca en la interacció persona-ordinador fets servir en, per exemple, estudis de usabilitat, d’experiència d’usuari o de la millora de tècniques de transmissió de vídeo. El comportament dels usuaris en aquests entorns ha atret l’atenció dels investigadors, però s’ha parat poca atenció a comparar el comportament dels usuaris entre diferents dispositius per reproduir entorns virtuals o vídeos en 360 graus. Nosaltres introduïm un sistema interactiu que hem fet servir per crear i reproduir entorns de realitat virtual i experiències basades en vídeos en 360 graus, que és capaç de recollir automàticament el comportament dels usuaris, de manera que el puguem analitzar. Hem estudiat el comportament recollit en la reproducció d’un entorn de realitat virtual amb aquest sistema i hem trobat diferències significatives en l’execució entre usuaris d’una interfície basada en Oculus Rift i d’una altra basada en un visor de RV mòbil semblant a la Google Cardboard: diferent temps entre interaccions, probablement causat per la necessitat de fer un gest amb la primera interfície; diferències en l’exploració espacial, perquè els usuaris de la primera interfície van triar romandre en una àrea de l’entorn; i diferències en l’orientació dels seus caps, ja que els usuaris d’Oculus tendiren a mirar cap a objectes físics de la instal·lació de l’experiment i els usuaris dels visors mòbils semblen influïts pels valors d’orientació inicials dels seus navegadors. Un segon estudi va ser executat amb les dades recollides amb aquest sistema, que va ser fet servir per reproduir un hipervídeo fet de vídeos en 360 graus, en què hem comparat el comportament dels usuaris entre quatre interfícies (dues basades en dispositius immersius i dues basades en dispositius no immersius) i dues categories de vídeos: hem trobat diferències significatives en l’exploració de l’espaitemps del vídeo, en la dispersió de l’orientació dels usuaris, en el moviment d’aquestes orientacions i en l’agrupació de les seves trajectòries, especialment entre diferents tipus de vídeo però també entre dispositius, ja que hem trobat que, en alguns casos, el comportament amb dispositius immersius és similar a causa de límits semblants en la interfície, que no són presents en dispositius no immersius, com amb un ratolí d’ordinador o la pantalla tàctil d’un mòbil. Finalment, hem reportat un model basat en una xarxa neuronal recurrent, que és capaç de classificar aquestes reproduccions de vídeos en 360 graus en els seus corresponents tipus de vídeo i interfície que s’ha fet servir amb una precisió de més del 90% amb només quatre segons de trajectòria d’orientacions; un altre model d’aprenentatge profund ha estat implementat per predir orientacions fins a dos segons en el futur a partir dels darrers segons d’orientació, amb uns resultats que han estat millorats fins a un 19% per un model comparable que aprofita el tipus de vídeo i el dispositiu que s’ha fet servir per reproduir-lo.[spa] La realidad virtual y las tecnologías que están relacionadas con ella se usan para muchos tipos de contenidos, como entornos virtuales o vídeos en 360 grados. Contenidos multimedia omnidireccionales e interactivos son consumidos con diversos dispositivos, como ordenadores, dispositivos móviles o aparatos especializados de realidad virtual. Los estudios del comportamiento de los usuarios con interfaces de ordenador son una parte importante de la investigación en la interacción persona-ordenador usados en, por ejemplo, estudios de usabilidad, de experiencia de usuario o de la mejora de técnicas de transmisión de vídeo. El comportamiento de los usuarios en estos entornos ha atraído la atención de los investigadores, pero se ha dedicado poca atención en comparar el comportamiento de los usuarios entre diferentes dispositivos para reproducir entornos virtuales o vídeos en 360 grados. Nosotros introducimos un sistema interactivo que hemos usado para crear y reproducir entornos de realidad virtual y experiencias basadas en vídeos de 360 grados, que es capaz de recoger automáticamente el comportamiento de los usuarios, de manera que lo podamos analizar. Hemos estudiado el comportamiento recogido en la reproducción de un entorno de realidad virtual con este sistema y hemos encontrado diferencias significativas en la ejecución entre usuarios de una interficie basada en Oculus Rift y otra basada en un visor de RV móvil parecido a la Google Cardboard: diferente tiempo entre interacciones, probablemente causado por la necesidad de hacer un gesto con la primera interfaz; diferencias en la exploración espacial, porque los usuarios de la primera interfaz permanecieron en un área del entorno; y diferencias en la orientación de sus cabezas, ya que los usuarios de Oculus tendieron a mirar hacia objetos físicos en la instalación del experimento y los usuarios de los visores móviles parecieron influidos por los valores iniciales de orientación de sus navegadores. Un segundo estudio fue ejecutado con los datos recogidos con este sistema, que fue usado para reproducir un hipervídeo compuesto de vídeos en 360 grados, en el que hemos comparado el comportamiento de los usuarios entre cuatro interfaces (dos basadas en dispositivos inmersivos y dos basadas en dispositivos no inmersivos) y dos categorías de vídeos: hemos encontrado diferencias significativas en la exploración espaciotemporal del vídeo, en la dispersión de la orientación de los usuarios, en el movimiento de estas orientaciones y en la agrupación de sus trayectorias, especialmente entre diferentes tipos de vídeo pero también entre dispositivos, ya que hemos encontrado que, en algunos casos, el comportamiento con dispositivos inmersivos es similar a causa de límites parecidos en la interfaz, que no están presentes en dispositivos no inmersivos, como con un ratón de ordenador o la pantalla táctil de un móvil. Finalmente, hemos reportado un modelo basado en una red neuronal recurrente, que es capaz de clasificar estas reproducciones de vídeos en 360 grados en sus correspondientes tipos de vídeo y la interfaz que se ha usado con una precisión de más del 90% con sólo cuatro segundos de trayectoria de orientación; otro modelo de aprendizaje profundo ha sido implementad para predecir orientaciones hasta dos segundos en el futuro a partir de los últimos segundos de orientación, con unos resultados que han sido mejorados hasta un 19% por un modelo comparable que aprovecha el tipo de vídeo y el dispositivo que se ha usado para reproducirlo

Understanding user interactivity for the next-generation immersive communication: design, optimisation, and behavioural analysis

Recent technological advances have opened the gate to a novel way to communicate remotely still feeling connected. In these immersive communications, humans are at the centre of virtual or augmented reality with a full sense of immersion and the possibility to interact with the new environment as well as other humans virtually present. These next-generation communication systems hide a huge potential that can invest in major economic sectors. However, they also posed many new technical challenges, mainly due to the new role of the final user: from merely passive to fully active in requesting and interacting with the content. Thus, we need to go beyond the traditional quality of experience research and develop user-centric solutions, in which the whole multimedia experience is tailored to the final interactive user. With this goal in mind, a better understanding of how people interact with immersive content is needed and it is the focus of this thesis. In this thesis, we study the behaviour of interactive users in immersive experiences and its impact on the next-generation multimedia systems. The thesis covers a deep literature review on immersive services and user centric solutions, before develop- ing three main research strands. First, we implement novel tools for behavioural analysis of users navigating in a 3-DoF Virtual Reality (VR) system. In detail, we study behavioural similarities among users by proposing a novel clustering algorithm. We also introduce information-theoretic metrics for quantifying similarities for the same viewer across contents. As second direction, we show the impact and advantages of taking into account user behaviour in immersive systems. Specifically, we formulate optimal user centric solutions i) from a server-side perspective and ii) a navigation aware adaptation logic for VR streaming platforms. We conclude by exploiting the aforementioned behavioural studies towards a more in- interactive immersive technology: a 6-DoF VR. Overall in this thesis, experimental results based on real navigation trajectories show key advantages of understanding any hidden patterns of user interactivity to be eventually exploited in engineering user centric solutions for immersive systems

Reward - based advertisement in online games: a win for advertisers, developers, and gamers

This study examines factors affecting gamers’ attitude towards reward-based advertisements (RBA) in online games. A conceptual model is developed based on the Ducoffe’s web advertising model and tested using a quantitative design through data collected from 532 online gamers in Fiji. Covariance-based structural equation modelling (CB-SEM) was employed to perform the analysis. Results reveal that informativeness, credibility, entertainment, and incentive positively influence advertisement value. Advertisement value was found to positively influences attitude towards RBA. The moderating factors of perceived competitiveness and gamer envy were found to strengthen the positive association between perceived advertisement value and attitude towards RBA. This study is novel is it is the first exploration of RBA in online gaming. In so doing, this study contributes to both marketing and gaming literature and provides valuable insight for marketers and game developers to influence customers to be more receptive to advertisements in online games

Gaming and luxury fashion: exploring factors driving gamers’ luxury virtual in - game fashion

This study investigates the factors driving gamers’ intention to purchase virtual luxury fashion in online games. The study’s conceptual framework is grounded in the social identity and social capital theory. A total of 468 responses were collected using an online survey from Fortnite players and analyzed using covariance-based structural equation modelling (CB-SEM). The results reveal that avatar identification was positively associated with perceived value, social presence, and intention to purchase virtual luxury fashion. Perceived value and social presence were positively associated with intending to purchase virtual luxury fashion. Brand love strengthened the positive association between the perceived value and social presence on the intention to purchase virtual luxury fashion. This study contributes to the marketing and information systems literature by offering the first insights into virtual luxury fashion in online games. The findings would assist game developers and marketers in better understanding gamer behaviour to capitalize on virtual luxury fashion