Creating a modern home: homeowners in post-war suburban Glasgow, 1945-1975

This thesis examines how married couples bought and created a modern home for their families in suburban Glasgow between 1945-1975. New homeowners were on the cusp of the middle-classes, buying in a climate of renters. As they progressed through the family lifecycle women’s return to work meant they became more comfortably ensconced within the middle-classes. Engaged with a process of homemaking through consumption and labour, couples transformed their houses into homes that reflected themselves and their social status. The interior of the home was focused on as a site of social relations. Marriage in the suburbs was one of collaboration as each partner performed distinct gender roles. The idea of a shared home was investigated and the story of ‘we’ rather than ‘I’ emerged from both testimony and contemporary literature. This thesis considers decision-making, labour and leisure to show the ways in which experiences of home were gendered. What emerged was that women’s work as everyday and mundane was overlooked and undervalued while husband’s extraordinary contributions in the form of DIY came to the fore. The impact of wider culture intruded upon the ‘private’ home as we see they ways in which the position of women in society influences their relationship to the home and their family. In the suburbs of post-war Glasgow women largely left the workforce to stay at home with their children. Mothers popped in and out of each other houses for tea and a blether, creating a homosocial network that was sociable and supportive unique to this time in their lives and to this historical context. Daily life was negotiated within the walls of the modern home. The inter-war suburbs of Glasgow needed modernising to post-war standards of modern living. ‘Modern’ was both an aesthetic and an engagement with new technologies within the house. Both middle and working-class practices for room use were found through the keeping of a ‘good’ or best room and the determination of couples to eat in their small kitchenettes. As couples updated their kitchen, the fitted kitchen revealed contemporary notions of modern décor, as kitchens became bright yellow with blue Formica worktops. The modern home was the evolution of existing ideas of modern combined with new standards of living. As Glasgow homeowners constructed their modern home what became evident was that this was a shared process and as a couple they placed their children central to all aspects of their lives to create not only a modern home, but that this was first and foremost a family home

Supporting collocated and at-a-distance experiences with TV and VR displays

Televisions (TVs) and VR Head-Mounted Displays (VR HMDs) are used in shared and social spaces in the home. This thesis posits that these displays do not sufficiently reflect the collocated, social contexts in which they reside, nor do they sufficiently support shared experiences at-a-distance. This thesis explores how the role of TVs and VR HMDs can go beyond presenting a single entertainment experience, instead supporting social and shared use in both collocated and at-a-distance contexts. For collocated TV, this thesis demonstrates that the TV can be augmented to facilitate multi-user interaction, support shared and independent activities and multi-user use through multi-view display technology, and provide awareness of the multi-screen activity of those in the room, allowing the TV to reflect the social context in which it resides. For at-a-distance TV, existing smart TVs are shown to be capable of supporting synchronous at-a-distance activity, broadening the scope of media consumption beyond the four walls of the home. For VR HMDs, collocated proximate persons can be seamlessly brought into mixed reality VR experiences based on engagement, improving VR HMD usability. Applied to at-a-distance interactions, these shared mixed reality VR experiences can enable more immersive social experiences that approximate viewing together as if in person, compared to at-a-distance TV. Through an examination of TVs and VR HMDs, this thesis demonstrates that consumer display technology can better support users to interact, and share experiences and activities, with those they are close to.

The role of context in image annotation and recommendation

With the rise of smart phones, lifelogging devices (e.g. Google Glass) and popularity of image sharing websites (e.g. Flickr), users are capturing and sharing every aspect of their life online producing a wealth of visual content. Of these uploaded images, the majority are poorly annotated or exist in complete semantic isolation making the process of building retrieval systems difficult as one must firstly understand the meaning of an image in order to retrieve it. To alleviate this problem, many image sharing websites offer manual annotation tools which allow the user to “tag” their photos, however, these techniques are laborious and as a result have been poorly adopted; Sigurbjörnsson and van Zwol (2008) showed that 64% of images uploaded to Flickr are annotated with < 4 tags. Due to this, an entire body of research has focused on the automatic annotation of images (Hanbury, 2008; Smeulders et al., 2000; Zhang et al., 2012a) where one attempts to bridge the semantic gap between an image’s appearance and meaning e.g. the objects present. Despite two decades of research the semantic gap still largely exists and as a result automatic annotation models often offer unsatisfactory performance for industrial implementation. Further, these techniques can only annotate what they see, thus ignoring the “bigger picture” surrounding an image (e.g. its location, the event, the people present etc). Much work has therefore focused on building photo tag recommendation (PTR) methods which aid the user in the annotation process by suggesting tags related to those already present. These works have mainly focused on computing relationships between tags based on historical images e.g. that NY and timessquare co-exist in many images and are therefore highly correlated. However, tags are inherently noisy, sparse and ill-defined often resulting in poor PTR accuracy e.g. does NY refer to New York or New Year? This thesis proposes the exploitation of an image’s context which, unlike textual evidences, is always present, in order to alleviate this ambiguity in the tag recommendation process. Specifically we exploit the “what, who, where, when and how” of the image capture process in order to complement textual evidences in various photo tag recommendation and retrieval scenarios. In part II, we combine text, content-based (e.g. # of faces present) and contextual (e.g. day-of-the-week taken) signals for tag recommendation purposes, achieving up to a 75% improvement to precision@5 in comparison to a text-only TF-IDF baseline. We then consider external knowledge sources (i.e. Wikipedia & Twitter) as an alternative to (slower moving) Flickr in order to build recommendation models on, showing that similar accuracy could be achieved on these faster moving, yet entirely textual, datasets. In part II, we also highlight the merits of diversifying tag recommendation lists before discussing at length various problems with existing automatic image annotation and photo tag recommendation evaluation collections. In part III, we propose three new image retrieval scenarios, namely “visual event summarisation”, “image popularity prediction” and “lifelog summarisation”. In the first scenario, we attempt to produce a rank of relevant and diverse images for various news events by (i) removing irrelevant images such memes and visual duplicates (ii) before semantically clustering images based on the tweets in which they were originally posted. Using this approach, we were able to achieve over 50% precision for images in the top 5 ranks. In the second retrieval scenario, we show that by combining contextual and content-based features from images, we are able to predict if it will become “popular” (or not) with 74% accuracy, using an SVM classifier. Finally, in chapter 9 we employ blur detection and perceptual-hash clustering in order to remove noisy images from lifelogs, before combining visual and geo-temporal signals in order to capture a user’s “key moments” within their day. We believe that the results of this thesis show an important step towards building effective image retrieval models when there lacks sufficient textual content (i.e. a cold start).