Mobile Applications for Automatic Object Recognition

Mobile Applications for Automatic Object Recognition

Danilo Avola, Gian Luca Foresti, Claudio Piciarelli, Marco Vernier, Luigi Cinque
Copyright: © 2019 |Pages: 13
DOI: 10.4018/978-1-5225-7598-6.ch073
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Abstract

In recent years, the technological improvements of mobile devices in terms of computational capacity, embedded sensors, natural interaction, and high-speed connection are enabling an ever-increasing number of designers to develop advanced mobile applications to be used in everyday life. Among these, the vision-based applications for the automatic object recognition (AOR) play a key role since enabling users to interact with the world around them in innovative way makes more productive and profitable their entertainment, learning, and working activities. The chapter is divided into four sections. The first one, “Background,” explores the most recent works in AOR mobile applications highlighting the feature extraction processes and the implemented classifiers. The second one, “MV Development Technologies,” provides an overview of the current frameworks used to support the mobile AOR applications. The third one, “Future Research Trends,” discusses the aims of the next generation of AOR applications. Finally, “Conclusion” concludes the chapter.
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Background

In the last decade, mobile devices have had ongoing and growing technological advances. Currently these devices, even those of low cost, have a set of hardware features that make them comparable with a wide range of desktop processing units. In fact, these mobile devices, with particular reference to those of the latest generation, present a set of significant improvements, including:

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    Multi-Core Processor (MCP): A single processor that contains several cores. This technology typical of common processing units (e.g., workstations, servers) allows mobile devices to rapidly process a large amount of data also improving the performance of running multiple applications.

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    Advanced Storage Capacity (ASC): A large amount of internal memory and the possibility to adopt external memories (e.g., compact flash, memory stick). This technology allows mobile devices to support both complex data and bulky applications.

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    Mobile Sensing (MS): The set of sensors embedded in a mobile device. This technology allows mobile devices to be equipped with a wide range of sensors, including: Red-Green-Blue (RGB) sensor (i.e., image camera), Global Position System (GPS) receiver (i.e., localization system), accelerometer sensor (i.e., proper acceleration “g-force”), gyroscope sensor (i.e., orientation system) and others. These sensors are used to acquire any type of information from both the external world (e.g., images, temperature, pressure) and user’s behavior (e.g., speed, locations, actions).

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    Natural User Interfaces (NUIs): The set of natural interfaces to favor the Human-Computer Interaction (HCI) between users and mobile devices. This technology allows users to adopt human-oriented interfaces (e.g., speech recognition, touch-screen interaction) to manage data and devices.

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    Fast Internet Connections (FICs): The set of information and communication technologies (ICTs) that allow devices to access to any type of resource, including: World Wide Web (WWW), cloud computing, dedicated networks and others.

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