Outsourcing labour to the cloud

Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

An evaluation tool for design quality: PFI sheltered housing

The complex procurement process entailed by the private finance initiative (PFI) means that clients need new capacities to manage their relationships with bidders and to assess project proposals if the desired level of design quality is to be achieved. To assist local authorities in their client role, a new Architectural Design Quality Evaluation Tool was developed. The aim was to improve the quality of design in residential sheltered housing, procured through the PFI. The tool was developed for and applied to a programme that will see the replacement of a local authority's entire sheltered housing stock. The tool has two functions: (1) to inform the client's assessment process and assist with the selection of the preferred bidding consortium through a series of stages in the PFI process; and (2) to improve the quality of all the submitted designs through an iterative process. Although several existing mechanisms are available for evaluating the performance attributes of buildings, few also tackle the less tangible amenity attributes, which are vital to the feeling of home. The new tool emphasizes the amenity attributes without neglecting performance

Example-Based Urban Modeling

The manual modeling of virtual cities or suburban regions is an extremely time-consuming task, which expects expert knowledge of different fields. Existing modeling tool-sets have a steep learning curve and may need special education skills to work with them productively. Existing automatic methods rely on rule sets and grammars to generate urban structures; however, their expressiveness is limited by the rule-sets. Expert skills are necessary to typeset rule sets successfully and, in many cases, new rule-sets need to be defined for every new building style or street network style. To enable non-expert users, the possibility to construct urban structures for individual experiments, this work proposes a portfolio of novel example-based synthesis algorithms and applications for the controlled generation of virtual urban environments. The notion example-based denotes here that new virtual urban environments are created by computer programs that re-use existing digitized real-world data serving as templates. The data, i.e., street networks, topography, layouts of building footprints, or even 3D building models, necessary to realize the envisioned task is already publicly available via online services. To enable the reuse of existing urban datasets, novel algorithms need to be developed by encapsulating expert knowledge and thus allow the controlled generation of virtual urban structures from sparse user input. The focus of this work is the automatic generation of three fundamental structures that are common in urban environments: road networks, city block, and individual buildings. In order to achieve this goal, the thesis proposes a portfolio of algorithms that are briefly summarized next. In a theoretical chapter, we propose a general optimization technique that allows formulating example-based synthesis as a general resource-constrained k-shortest path (RCKSP) problem. From an abstract problem specification and a database of exemplars carrying resource attributes, we construct an intermediate graph and employ a path-search optimization technique. This allows determining either the best or the k-best solutions. The resulting algorithm has a reduced complexity for the single constraint case when compared to other graph search-based techniques. For the generation of road networks, two different techniques are proposed. The first algorithm synthesizes a novel road network from user input, i.e., a desired arterial street skeleton, topography map, and a collection of hierarchical fragments extracted from real-world road networks. The algorithm recursively constructs a novel road network reusing these fragments. Candidate fragments are inserted into the current state of the road network, while shape differences will be compensated by warping. The second algorithm synthesizes road networks using generative adversarial networks (GANs), a recently introduced deep learning technique. A pre- and postprocessing pipeline allows using GANs for the generation of road networks. An in-depth evaluation shows that GANs faithfully learn the road structure present in the example network and that graph measures such as area, aspect ratio, and compactness, are maintained within the virtual road networks. To fill empty city blocks in road networks we propose two novel techniques. The first algorithm re-uses real-world city blocks and synthesizes building footprint layouts into empty city blocks by retrieving viable candidate blocks from a database. We evaluate the algorithm and synthesize a multitude of city block layouts reusing real-world building footprint arrangements from European and US-cities. In addition, we increase the realism of the synthesized layouts by performing example-based placement of 3D building models. This technique is evaluated by placing buildings onto challenging footprint layouts using different example building databases. The second algorithm computes a city block layout, resembling the style of a real-world city block. The original footprint layout is deformed to construct a textit{guidance map}, i.e., the original layout is transferred to a target city block using warping. This guidance map and the original footprints are used by an optimization technique that computes a novel footprint layout along the city block edges. We perform a detailed evaluation and show that using the guidance map allows transferring of the original layout, locally as well as globally, even when the source and target shapes drastically differ. To synthesize individual buildings, we use the general optimization technique described first and formulate the building generation process as a resource-constrained optimization problem. From an input database of annotated building parts, an abstract description of the building shape, and the specification of resource constraints such as length, area, or a number of architectural elements, a novel building is synthesized. We evaluate the technique by synthesizing a multitude of challenging buildings fulfilling several global and local resource constraints. Finally, we show how this technique can even be used to synthesize buildings having the shape of city blocks and might also be used to fill empty city blocks in virtual street networks. All algorithms presented in this work were developed to work with a small amount of user input. In most cases, simple sketches and the definition of constraints are enough to produce plausible results. Manual work is necessary to set up the building part databases and to download example data from mapping services available on the Internet

Store layout effects on consumer behavior in 3D online stores

Purpose: Positioned in the e-retailing field, this study aims to investigate the effect of the retail store’s atmosphere on consumer behavior in 3D online shopping environments, focusing on store layout as a critical influential factor. Design/methodology/approach: The research uses a mixed research method approach that includes two complementary studies. First, a three-round Delphi study with domain experts is used to develop a store layout classification scheme (Study 1), resulting in five distinct types of store layout. Subsequently, 3D online retail stores that use the five layouts are designed and developed. These serve as treatments of a laboratory experimental design, which is used to assess layout impact on a number of attitudinal and behavioral variables (Study 2). Findings: Five distinct types of store layout have been identified in Study 1, and their distinctive features are presented. The findings of Study 2 indicate that online shopping enjoyment, entertainment and ease of navigation are influenced by the store layout types of 3D online environments. Specifically, the “avant-garde” layout type facilitates the ease of navigation of customers in the store and provides a superior online customer experience. The “warehouse”’ adopts long aisles for the display of products, which simplifies the comparison of products, whereas the “boutique” layout was found to be the best in terms of shopping enjoyment and entertainment. The “department” layout shares many common characteristics with traditional department stores, providing an entertaining and enjoyable store, whereas the “pragmatic” layout emphasizes low system requirements. Practical implications: The paper presents characteristics that make store layouts effective for different aspects of online customers’ experience and identifies opportunities that 3D online store designers and retailers can explore for the provision of enhanced, customized services to online customers. Originality/value: This paper examines recent technological developments in store design and visual merchandising. It identifies five layout types of 3D online stores, which are different from those of brick–and–mortar and 2D online stores, and investigates their impact on consumer behavior. Further, the paper examines how each layout type influences online shopping enjoyment, entertainment, ease of navigation, online customer experience and, in turn, purchase and word-of-mouth intentions. Finally, the paper examines the moderating role of telepresence. Individuals with high sense of telepresence conceive 3D environments as “real” and are more concerned about the attributes that trigger the sense of enjoyment they experience while browsing

Virtually the same: understanding consumer experiences in the digital retail environment

Retailing is heralded as undergoing a sea-change – with consumers touted as moving their purchasing from high-street to digital store. This is evident in industry commentary: Physical retail will no longer be a channel for buying... Rather, these spaces will act as living, breathing physical portals into brand and product experiences. They will become places we go to learn, be inspired, see and try new things, experiment and co-create… My advice to retailers is to stop thinking “stores” and start thinking stories. Stop thinking “product” and start thinking productions. Doug Stephens, 17 June 2018: https://businessoffashion.com/articles/opinion/to-save-retail-let-it-die Irrespective of this prophecy’s truth, understanding consumers’ relationships to what is undoubtedly a changing retail landscape, where the digital environment is becoming more central, is critical. Extensive research considers the physical or virtual retail environment. This is variously framed, drawing on themes including: retail atmospherics (e.g. Helmefalk & Hultén, 2017); servicescapes (e.g. Ballantyne & Nilsson 2017); store environments, and the sensory [often stimulus-organism-response frameworks] (e.g. Garaus, 2016; Fujiwara, Resnick, Cassidy, & Brown, 2017). Research in this domain has yet to develop an integrated position on how to comprehend consumer retail environment experiences– particularly when that environment is virtual

3D Object Representations for Recognition.

Object recognition from images is a longstanding and challenging problem in computer vision. The main challenge is that the appearance of objects in images is affected by a number of factors, such as illumination, scale, camera viewpoint, intra-class variability, occlusion, truncation, and so on. How to handle all these factors in object recognition is still an open problem. In this dissertation, I present my efforts in building 3D object representations for object recognition. Compared to 2D appearance based object representations, 3D object representations can capture the 3D nature of objects and better handle viewpoint variation, occlusion and truncation in object recognition. I introduce three new 3D object representations: the 3D aspect part representation, the 3D aspectlet representation and the 3D voxel pattern representation. These representations are built to handle different challenging factors in object recognition. The 3D aspect part representation is able to capture the appearance change of object categories due to viewpoint transformation. The 3D aspectlet representation and the 3D voxel pattern representation are designed to handle occlusions between objects in addition to viewpoint change. Based on these representations, we propose new object recognition methods and conduct experiments on benchmark datasets to verify the advantages of our methods. Furthermore, we introduce, PASCAL3D+, a new large scale dataset for 3D object recognition by aligning objects in images with 3D CAD models. We also propose two novel methods to tackle object co-detection and multiview object tracking using our 3D aspect part representation, and a novel Convolutional Neural Network-based approach for object detection using our 3D voxel pattern representation. In order to track multiple objects in videos, we introduce a new online multi-object tracking framework based on Markov Decision Processes. Lastly, I conclude the dissertation and discuss future steps for 3D object recognition.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120836/1/yuxiang_1.pd

Exploratory shopping: attention affects in-store exploration and unplanned purchasing

A fundamental function of retailing is to bring products into the view of shoppers, because viewing products can activate forgotten or new needs. Retailers thus employ various strategies to entice shoppers to explore the product assortment and store environment, in the hopes of stimulating unplanned purchasing. Here we investigate consumers’ breadth of attention as a mechanism of such in-store exploration and hence of unplanned purchasing. Specifically, attentional breadth is the focus that is directed to a wider or more limited area in processing visual scenes. In a series of lab and field experiments we show that shoppers’ attentional breadth activates an exploratory mindset that stimulates visual and physical exploration of shopping environments, ultimately affecting their product choices and unplanned purchasing. We also show that more impulsive buyers are more susceptible to these effects. These results complement and constrain prior theorizing on mindset theory, attention, store exploration, and unplanned purchasing, all of which are of practical importance to both retailers and consumers

Realistic reconstruction and rendering of detailed 3D scenarios from multiple data sources

During the last years, we have witnessed significant improvements in digital terrain modeling, mainly through photogrammetric techniques based on satellite and aerial photography, as well as laser scanning. These techniques allow the creation of Digital Elevation Models (DEM) and Digital Surface Models (DSM) that can be streamed over the network and explored through virtual globe applications like Google Earth or NASA WorldWind. The resolution of these 3D scenes has improved noticeably in the last years, reaching in some urban areas resolutions up to 1m or less for DEM and buildings, and less than 10 cm per pixel in the associated aerial imagery. However, in rural, forest or mountainous areas, the typical resolution for elevation datasets ranges between 5 and 30 meters, and typical resolution of corresponding aerial photographs ranges between 25 cm to 1 m. This current level of detail is only sufficient for aerial points of view, but as the viewpoint approaches the surface the terrain loses its realistic appearance. One approach to augment the detail on top of currently available datasets is adding synthetic details in a plausible manner, i.e. including elements that match the features perceived in the aerial view. By combining the real dataset with the instancing of models on the terrain and other procedural detail techniques, the effective resolution can potentially become arbitrary. There are several applications that do not need an exact reproduction of the real elements but would greatly benefit from plausibly enhanced terrain models: videogames and entertainment applications, visual impact assessment (e.g. how a new ski resort would look), virtual tourism, simulations, etc. In this thesis we propose new methods and tools to help the reconstruction and synthesis of high-resolution terrain scenes from currently available data sources, in order to achieve realistically looking ground-level views. In particular, we decided to focus on rural scenarios, mountains and forest areas. Our main goal is the combination of plausible synthetic elements and procedural detail with publicly available real data to create detailed 3D scenes from existing locations. Our research has focused on the following contributions: - An efficient pipeline for aerial imagery segmentation - Plausible terrain enhancement from high-resolution examples - Super-resolution of DEM by transferring details from the aerial photograph - Synthesis of arbitrary tree picture variations from a reduced set of photographs - Reconstruction of 3D tree models from a single image - A compact and efficient tree representation for real-time rendering of forest landscapesDurant els darrers anys, hem presenciat avenços significatius en el modelat digital de terrenys, principalment gràcies a tècniques fotogramètriques, basades en fotografia aèria o satèl·lit, i a escàners làser. Aquestes tècniques permeten crear Models Digitals d'Elevacions (DEM) i Models Digitals de Superfícies (DSM) que es poden retransmetre per la xarxa i ser explorats mitjançant aplicacions de globus virtuals com ara Google Earth o NASA WorldWind. La resolució d'aquestes escenes 3D ha millorat considerablement durant els darrers anys, arribant a algunes àrees urbanes a resolucions d'un metre o menys per al DEM i edificis, i fins a menys de 10 cm per píxel a les fotografies aèries associades. No obstant, en entorns rurals, boscos i zones muntanyoses, la resolució típica per a dades d'elevació es troba entre 5 i 30 metres, i per a les corresponents fotografies aèries varia entre 25 cm i 1m. Aquest nivell de detall només és suficient per a punts de vista aeris, però a mesura que ens apropem a la superfície el terreny perd tot el realisme. Una manera d'augmentar el detall dels conjunts de dades actuals és afegint a l'escena detalls sintètics de manera plausible, és a dir, incloure elements que encaixin amb les característiques que es perceben a la vista aèria. Així, combinant les dades reals amb instàncies de models sobre el terreny i altres tècniques de detall procedural, la resolució efectiva del model pot arribar a ser arbitrària. Hi ha diverses aplicacions per a les quals no cal una reproducció exacta dels elements reals, però que es beneficiarien de models de terreny augmentats de manera plausible: videojocs i aplicacions d'entreteniment, avaluació de l'impacte visual (per exemple, com es veuria una nova estació d'esquí), turisme virtual, simulacions, etc. En aquesta tesi, proposem nous mètodes i eines per ajudar a la reconstrucció i síntesi de terrenys en alta resolució partint de conjunts de dades disponibles públicament, per tal d'aconseguir vistes a nivell de terra realistes. En particular, hem decidit centrar-nos en escenes rurals, muntanyes i àrees boscoses. El nostre principal objectiu és la combinació d'elements sintètics plausibles i detall procedural amb dades reals disponibles públicament per tal de generar escenes 3D d'ubicacions existents. La nostra recerca s'ha centrat en les següents contribucions: - Un pipeline eficient per a segmentació d'imatges aèries - Millora plausible de models de terreny a partir d'exemples d’alta resolució - Super-resolució de models d'elevacions transferint-hi detalls de la fotografia aèria - Síntesis d'un nombre arbitrari de variacions d’imatges d’arbres a partir d'un conjunt reduït de fotografies - Reconstrucció de models 3D d'arbres a partir d'una única fotografia - Una representació compacta i eficient d'arbres per a navegació en temps real d'escenesPostprint (published version