Presentación Social Estatus y estilo*

Motion, also known as Photogrammetry [338], 3D Scanning [55], often called laser scanning, and topographical techniques [314].

In this category, navigation through avatars is completely absent as the aim is to provide the ability to interact with the 3D models from different vantage points (i.e. zooming in and out, panning and rotating).

Well-known social web repositories such as Sketchfab [374], Microsoft remix3d [102] and Google Poly [170] can host myriad types of 3D models on the web.

3. The third category takes the form of spherical/stereoscopic media, which can constitute spherical image scenery such as Panoramas or Photospheres [18] (also known as 360◦images). Spherical media can also consist of 360◦ videos [323] (also known as Videospheres). Famous social web repositories for 3D image scenery such as Roundme [343] and Google Poly [170] allow users to upload and share Photospheres and tours of Photospheres. Social Video repositories, such as YouTube [172], allow users to upload, playback and stream 360◦ videos.

1.2

Motivation

3D Web content is becoming an integral part of any Web-Based Virtual Museum (WBVM) [271]. Furthermore, mobile devices are being used more and more in the domain of virtual museums and cultural heritage [177, 344]. Choreographing and presenting 3D Web components across multiple platforms (mobile devices, tablets and personal computers) and network regimes (WiFi, Ethernet, 4G, 3G and 2G) present a significant challenge yet to overcome.

The challenge is to achieve a good user Quality of Experience (QoE) across all these platforms which have different characteristics and capabilities. This means that different levels of fidelity and complexity of media may be appropriate. Therefore servers hosting those media types need to adapt to the capabilities of a wide range of networks and devices.

To achieve this, there is a need to design and develop an adaptive QoS and QoE aware engine that allows Web-Based Virtual Museums to deliver the best user experience across those platforms.

In order to ensure effective adaptivity, we need to know what matters to the user in terms of fidelity and in terms of QoS such as responsiveness of the 3D Web categories used in Web-Based Virtual Museums (WBVMs). We need to know that, for different media types, there are perceptible and particular qualities in terms of service and in terms of user experience.

The way in which this thesis proposes to approach achieving adaptivity in Web-Based Virtual Museums is by supplementing existing semantic 3D Web metadata vocabularies with QoS-related metadata. This metadata will make available the characteristics of the media to applications which will enable them to make decisions about what is the right resolution to fetch to client devices.

An“intermediate” approach as described in [175] was used to keep the descriptions of 3D Web artefacts separate from them. This allows us to have complementary information about digital artefacts that helps us in improving the Quality of Service delivered and allows us easily to use management tools to search and locate 3D media information.

It would be useful for WBVMs to represent 3D scenes and artefacts across multiple platforms and network regimes at the best possible user experience.

An important characteristic of virtual museums is the ability to document and supplement additional information to digital artefacts. This is done by enriching digital artefacts semantically with what is called“Metadata”. Metadata is data about data or data that comes alongside with other data.

Meta a prefix coming from Greek origins meansalongside or with. This prefix was also used in some contexts to mean“transcendental” or“beyond a certain realm”. Metadata normally are presented in the form of attributes or characteristics of artefacts. Such metadata are machine-readable (i.e. can be read and processed by applications) and are human-readable.

Metadata play important roles in the context of virtual museums:

1. They facilitate the task of searching and retrieving digital artefacts from repositories thus making the process more intelligent and efficient.

1.2. MOTIVATION 21

between them.

3. They document important information pertaining to their provenance, authorship, contributorship, creation and issuance dates, accrual method and periodicity, access rights, heritage significance, copyright licences among many other important characteristics.

“Paradata” can also be supplemented to digital heritage artefacts. “Paradata” are all the processes or methodologies of how particular data came to be. Paradata for instance, in the context of 3D Digital Heritage artefacts, detail all methodological and processual information that underpins the 3D digitisation and visualisation. They can include the people involved, the duration of the process, the time of the day of when the process is conducted in the case of digitisation and the equipment and software used [76]. In addition, they document also any intellectual research capital [35, 110, 111].

QoS metadata of 3D Web components could be derived from 3D Web data charac- teristics and may constitute information about 3D Web components such as size, fidelity (i.e. resolution), Average Frame Rate, and compression types among other data that would characterise a specific 3D Web component in question.

A Web-Based Virtual Museum for instance, would have different instantiations (i.e. resolutions) of particular 3D Web components and would choose the “best possible instantiation” with the“best possible resolution” to fetch depending on the graphical capabilities of the client devices, depending on the network regimes and depend on QoE considerations. More importantly, the decisions are made based on the results that were gathered from the Quality of Service and Quality of Experience studies conducted in this research corpus, emphasising the pertinence of the subjective perception of fidelity of DH 3D Web content from users’perspective.

Can casual WBVMs users notice the difference in perception of resolution between a 3D model that has a fidelity of 5 million faces and another same exact replica which has a fidelity of 450 thousand faces or even less on a 5 inch screen mobile device? If not why send the 3D model with the 5 million faces? That would mean overcommitting unnecessary hardware resources that do not add much to the user experience, in addition to resulting in lower performance and higher download and processing time. The subjective perception of fidelity is examined in Chapter 5 and the results were published in [28].

The client hardware and software capabilities would be determined by how much the client device can render graphics (for example, by doing a WebGL benchmark), by the type of the device (mobile or non-mobile), size and resolution of the screen, and its operating system among other characteristics.

Network conditions would be the type of the network the client device is connected to (WiFi, Ethernet, 4G, 3G), the download speed, upload speed and latency among other network characteristics.

The three types of information feed a QoS and QoE aware adaptive engine (Hannibal) that decides automatically what is the best 3D Web component instantiation to fetch to a particular client device depending on its“situation”(graphical capability and network conditions). Figure 1.5 shows the input and the output of the adaptive engine.

Hannibal Adaptive Engine 3D Web QoS-Related Metadata

Client Device Hardware Software Capabilities

Network Conditions

Sending the right Resolution

Figure 1.5: Hannibal QoS & QoE Aware Adaptive Engine

Figure 1.6 shows the overall work conducted in this thesis. A set of QoS/QoE experiments on 3D Web components will feed the design and implementation of an adaptive engine (Hannibal) which is implemented in a WBVM.