Fast Single Shot Detection and Pose Estimation

For applications in navigation and robotics, estimating the 3D pose of objects is as important as detection. Many approaches to pose estimation rely on detecting or tracking parts or keypoints [11, 21]. In this paper we build on a recent state-of-the-art convolutional network for slidingwindow detection [10] to provide detection and rough pose estimation in a single shot, without intermediate stages of detecting parts or initial bounding boxes. While not the first system to treat pose estimation as a categorization problem, this is the first attempt to combine detection and pose estimation at the same level using a deep learning approach. The key to the architecture is a deep convolutional network where scores for the presence of an object category, the offset for its location, and the approximate pose are all estimated on a regular grid of locations in the image. The resulting system is as accurate as recent work on pose estimation (42.4% 8 View mAVP on Pascal 3D+ [21] ) and significantly faster (46 frames per second (FPS) on a TITAN X GPU). This approach to detection and rough pose estimation is fast and accurate enough to be widely applied as a pre-processing step for tasks including high-accuracy pose estimation, object tracking and localization, and vSLAM

Digital business models in cultural tourism

Purpose Digitalization had a relevant impact on the cultural tourism sector, both demand and supply. If, on the one hand, advances in digital technologies provided tourists with new mobile services able to amplify the cultural experience, on the other hand, they catalyzed the development of new business models by digital enterprises. This paper has a twofold purpose: to detect business models and key characteristics of mobile apps for cultural tourism and to analyze the offering of app-based services in this sector. Design/methodology/approach The authors defined a methodology to identify, characterize and analyze a particular category of digital products for cultural tourism: app-based services. They are studied in terms of value creation, proposition and capture with the aim to identify the distinctive features of business models. As a result, the authors identified a classification framework on three main dimensions, namely "how to exploit mobile app features to create value for cultural tourists" (value creation), "which valuable services are delivered to cultural tourists" (value proposition) and "how companies are rewarded for the value they offered" (value capture). The authors apply the framework to perform a situation analysis of app-based services in the cultural tourism market. Findings The analysis highlights that digital enterprises offering app-based services do not fully exploit advances in technologies about users' value requirements. Hence, the results of our work suggest some directions that digital enterprises may follow to better exploit mobile app technology. Originality/value To date, little research has been devoted to investigating cultural tourism business models involving the exploitation of mobile app-based services. This research provides a useful framework to analyze fundamental aspects of business models in this sector. Such a framework represents a practical tool that provides fruitful insights for the design of a new generation of app-based services within the so-called "Internet of things" domain

Rethinking tourism destinations: collaborative network models for the tourist 2.0

In the increasingly saturated tourism market, an effective tourism destination management is essential to support competitive and sustainable growth. The topic becomes interesting in light of the spread of the collaborative network (CN) organisational models and the massive diffusion of web 2.0 and mobile technology. The formers have proven to give concrete opportunities of development in many industrial sectors, the latter has been changing the way tourists experience a destination. Even if several case studies of CNs in tourism are known, a comprehensive study of how tourism destinations can benefit of CN models and enabling technologies is not present; especially in the effort to help tourism destinations in setting up services able to actively support each phase of the tourist 2.0 lifecycle. In this paper we highlight how CN models are able to support the tourism destination management in order to gain competitiveness for local areas, to improve flexibility in services provision and to give tourists the possibility to live an augmented tourism experience. Furthermore, a review of the most suitable forms of collaborative network for tourism destination and their ways to actively support the augmented experience of the tourist 2.0 are proposed

Recognizing Fine-Grained Object Instances for Robotics Applications

State-of-the-art object recognition systems, and computer vision methods in general, are getting better and better at a variety of tasks. Many of these techniques focus on general object categories, like person or bottle, and use many hundreds or thousands of training examples per category. Some domains, such as robotics, require recognition of fine-grained object instances, such as a 16oz. bottle of Coke, and only have access to limited training data. In this work we look at how to build data and adapt successful computer vision techniques for fine-grained object recognition tasks. Our Active Vision Dataset is the first deep-learning scale dataset for instance detection and motion simulation using real images. Our Target Driven Instance Detection method uses a siamese convolutional neural network to focus on specific fine-grained object instances, and has the capacity to generalize to instances outside its training set. Our SymGan method used the Generative Adversarial Network paradigm to train a 3D object orientation predictor that is robust to object symmetries.Doctor of Philosoph

Enabling Virtual Organizations in a Technological District

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Sustainable Development for Rural Areas: A Survey on the Agritourism Rural Networks

The topic of sustainable growth is becoming central in the debate over the rural development policies. Rural communities can completely fulfil the new challenges in the area of sustainability only with the implementation of innovative forms of collaborations among their business networks. In this work, we consider a particular form of business collaboration arising within rural communities, namely Agritourism Rural Network (ARN). In an ARN, a farm, providing agritourism activities, represents a touchpoint between a network of business and organizations in a rural area and tourists interested in enjoying the local territory. With the aim to deeper the extend of the agritourism phenomenon in a rural region and the potential of the related ARNs in being means of sustainable development, we report main results of an empirical survey carried out in 2016 on a sample of 105 agritourism farms all belonging to the same region (Calabria, Italy). Results confirm our intuitions about the importance at farm level of setting agritourism activities and their impact for the ARN related to the farm and for the sustainable development of a local community as a whole

Application areas of social media in external B2B transactions - An empirical analysis of Finnish technology industry

Despite the topic popularity, social media research is still limited, and focuses largely on the role of consumer-to-consumer (C2C) and business-to-consumer (B2C) domains. In many parts, the B2C social media practices are not directly useful for inter-organizational and B2B purposes. Main aim of this paper is to help to understand the current application areas of social media especially in external B2B transactions. This is carried out by an extensive survey to companies representing the technology industry, which are operating purely in B2B markets, having only other companies as customers. We wanted to understand how industrial B2B companies currently apply social media in their own inter-organizational applications, which types of potential they see in social media in this context, and what kind of support they experience their companies to need for better adopting social media together with their customers and partners. A population of 2488 Finnish decision-makers were observed from the Federation of Finnish Technology Industries. From the answers of 143 different companies, 125 companies represented wholly (100%) B2B markets, which were chosen as the sample of this study. Researches on social media, especially survey-based studies, have not focused particularly on B2B companies only, especially on the inter-organizational applications of social media in B2B’s. Except for the B2B-marketing oriented study of Michaelidou et al., (2011), and study of social media utilization in B2B-relationships by Pettersson et al. (2014). This study extends the previous studies especially by creating new understanding on the maturity of social media integration to business, organizational business problems that companies perceive that can be solved with social media, and approaches that can support social media adoption in B2B companies. Managerially, the results can be used, for instance, to better understand the various types of possibilities of applying social media in the inter-organizational use in B2Bs, which are currently only superficially understood by a significant part of managers. This can help to support and facilitate external social media use in B2B