The goal of this conference is to provide an international forum for presenting recent research results on multimedia for mobile devices, and to bring together experts from both academia and industry for a fruitful exchange of ideas and discussion on future challenges. The authors are encouraged to submit work-in-progress papers as well as updates on previously reported systems. Outstanding papers may be recommended for the publication in the Journal Electronic Imaging or the Journal of Imaging Science and Technology.
Chatbots are computer programs that execute protocols for supporting human-machine conversations and perform various functions such as searching the web, ordering food, making appointments, and many more. To facilitate timely responses and actions, and enable interactive human-like conversations, chatbots require Natural Language Processing (NLP) to understand user's messages and respond appropriately. NLP is an area of computer science and artificial intelligence concerned with the interactions between computers and human languages. Google Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Dash Messaging is a smart chatbot platform that enables creation of chatbots based on the provided protocol for long-term conversations. In this paper, we discuss how to integrate Google Dialogflow NLP service to a case study chatbot launched with our Dash Messaging platform.
In recent years, localization systems have gained significance in the indoor environment because they are used at airports, highrise buildings, and parking garages. The performance of traditional localization technologies like global navigation satellite system (GNSS) degrades in the indoor environment because of the strong presence of multipath components, low received signal strength, and strong signal attenuation. Additionally, indoor localization techniques like trilateration and triangulation have limitations because these techniques require a direct line-of-sight environment and need multiple access points (APs). Thus, WLAN fingerprinting-based indoor localization has gained popularity due to its stable performance and being widely available. The general fingerprinting approach is received signal strength-based, which has performance limitations due to signal fluctuations and multipath components. Channel state information (CSI) based-fingerprinting has proven more stable in indoor localization. In this paper, we present the performance study of CSI based fingerprinting in three different scenarios: no, fixed, and moving multipath components. We utilize artificial neural network(ANN) and compare the localization error of each scenario with received signal strength-based fingerprinting.
Morphing is a well-researched topic in computer graphics and image processing. Unlike cross-fading, morphing transforms a source image into a target image using distortions and the adjustment of predefined features (control points). This transition is intended to create results that are as realistic as possible, and it happens notably when the face on the source and target images does not differ too much. Therefore, the typical morphing process consists of warping essential image elements (e.g., facial features such as eyes, mouth, and facial contours) in the source and target image with the help of selected control points in such a way that these areas can be brought into conformity with each other or align themselves. For effects as close to reality as possible, the source and target images must not differ too much. The training course developed for this work is intended to introduce the dangers posed by the malicious manipulation of facial photographs, the so-called morphing attack. An algorithm matches the images of two different people so that the resulting facial image combines the identification features of both people. Research has shown that these images are difficult for the human eye to distinguish from real, unaltered photographs. The face morphing attack exploits the weakness in the application for identification. If a morphed passport photo remains undiscovered, a genuine identity document with a manipulated photo is issued that may allow two different persons to cross a border without authorization. This targeted training course consists of 10 modules for a one-week training course and is designed to help identify morphed facial images and reduce their acceptance at ID and passport control.
Self-driving cars are gradually making their way into road traffic and represent the main component of the new form of mobility. Major companies such as Tesla, Google, and Uber are researching the continuous improvement of self-driving vehicles and their reliability. Therefore, it is of great interest for trained professionals to deal with and understand the principles and requirements for autonomous driving. This paper aims to describe the new concept of a Bachelor / Master level university course for automotive technology students to address new mobility and self-driving cars. For the practice-oriented course, hardware in a low budget range (US $80) was used, which nevertheless has all the necessary sensors and requirements for a comprehensive practical introduction to the topic of self-driving automotive technology. The modular structure of the course contains lectures and exercises on the following topics: The first Exercise deals with the construction and modification of the Car-Kit, followed by the setup of the used Raspberry Pi. Since the car kit and Raspberry Pi are ready to use, the third exercise will steer the car remotely. The autonomous lane lectures and exercises follow this navigation with color spaces and masking, the Canny edge detection, Hough transform, steering, and stabilization.
The hybridization of renewable energy resources is a known topic in sustainable technology. Many projects are going on based on the topic. The use of Photovoltaic, wind energy, and other renewable resources can be helpful to optimize the load in the utility grid. Countries like Europe and other western countries have electricity storage, whether the developing countries are still struggling to make sure the stable utility grid connection to the distribution network system. In this research, we would like to discuss the different energy production processes sustainably. As we know, the energy sources are volatile and cannot always assure stable production to keep the requirements or demand properly. We want to use the combination of the sources in a way so that we can make the balance between the demand and the supply system. This research will be an overview in terms of technical and financial sites. Also, by using the different combinations of the Internet of things and data analysis method, we will see the correlation between the different sources and their production. Based on the production data, we can determine the financial feasibility and the outcome of the system. The main problem of renewable energy sources is uncertainty. In terms of wind energy, the velocity is also not stable according to the location. We want to show a predictive model by using the intelligent formula by which we can maintain the hybrid system. The production data from different sources will tell us their contribution to the system. This contribution will help us monitor the system and control which sources have more contribution on the demand side. The predictive model will have consisted of renewable sources such as photovoltaic, wind, utility grid, and inverter systems. In the research, the tool such as Artificial Intelligence can be implemented by sustainable management. The arrangement information is prepared to extricate data and based on resources. The renewable sources data are variant according to their location and it has an impact in terms of energy production. Data acquisition and analysis could help the current technologies such as smart grid, microgrid, and their control systems. This exploration aims to introduce a predictive foundation for the management of enormous volumes of data through large Information instruments (sensors) to help the coordination of environmentally friendly power. The main difference between the conventional electricity system and the renewable energy system is the variability of sources, with conventional sources such as utility grids and diesel generators and renewable sources consisting of photovoltaic (PV), wind, etc.
According to our recent paper [1], the concept of creating a still image panorama with the additional inclusion of video footage up to 30K resolution has proven to be successful in various application examples. However, certain aspects of the production pipeline need some optimization, especially the color workflow and the spatial placement of the video content. This paper aims to compare two workflows to overcome these problems. In particular, the following two methods are described in detail: 1) Improving the current workflow with the Canon EOS D5 Mark IV camera as the central device, 2) Establishing a new workflow using the new possibilities of the Apple iPhone 12 Pro MAX. The following aspects are the subject of our investigation: a) The fundamental idea is to use the ACES as the central color management system. It is investigated if the direct import from RAW to ACEScg via dcraw and rawtoaces shows advantages. In addition, the conversion from Dolby Vision to ACES for the video processing is investigated, and the result is evaluated. Furthermore, the influence of stitching programs (e.g., PTGUI) on the color workflow is observed and optimized. b) The second part of the paper deals with the spatial integration of the videos into the still panoramas. Due to the different crop factors, specific focal lengths must be applied when using the Canon EOS D5 Mark IV; this distorts the image and video materials differently and makes it difficult to place the video footage in the panorama. We investigate if the usage of the lens distortion removal algorithm improves results. Furthermore, the comparison of the performance and capabilities of the Apple iPhone 12 Pro MAX is also evaluated regarding this aspect. Finally, the recorded resolution of detailed vegetation and foliage in video footage is compared. The paper summarizes the results of the new proposed workflow and indicates necessary further investigation. [1] Hasche, Eberhard; Benning, Dominik; Karaschewski, Oliver; Carstens, Florian; Creutzburg, Reiner: Creating high-resolution 360-degree single-line 25K video content for modern conference rooms using film compositing techniques. In: Electronic Imaging, Mobile Devices and Multimedia: Technologies, Algorithms & Applications 2020, pp. 206-1-206-14(14), https://doi.org/10.2352/ISSN.2470-1173.2020.3.MOBMU-206
360-degree image and movie content has gained popularity over the media and the MICE (Meeting, Incentive, Conventions, and Exhibitions) industry in the last few years. There are three main reasons for this development. First, on the one hand, it is the immersive character of this media form, and, on the other hand, the development of recording and presentation technology has made significant progress in terms of resolution and quality. Third, after a decade of dynamic rising, the MICE Industry focuses on a disruptive change for more digital-based solutions. 360-degree panoramas are particularly widespread in VR and AR technology. However, despite the high immersive potential, these forms of presentation have the disadvantage that the users are isolated and have no social contact during the performance. Therefore, efforts have been made to project 360-degree content in specially equipped rooms or planetariums to enable a shared experience for the audience. One application area for 360-degree panoramas and films is conference rooms in hotels, conference centers, and any other venues that create an immersive environment for their clients to stimulate creativity. This work aims to overview the various application scenarios and usability possibilities for such conference rooms. In particular, we consider applications in construction, control, tourism, medicine, art exhibition, architecture, music performance, education, partying, organizing and carrying out events, and video conferencing. These applications and use scenarios were successfully tested, implemented, and evaluated in the 360-degree conference room “Dortmund” in the Hotel Park Soltau in Soltau, Germany. Finally, the advantages, challenges, and limitations of the proposed method are described.
Recently human-machine digital assistants gained popularity and commonly used in question-and-answer applications and similar consumer-supporting domains. A class of more sophisticated digital assistants employing longer dialogs follow the trend, and there are several commercial platforms supporting their prototyping such as Google DialogFlow, Manychat, Chatfuel, Amazon Lex, etc. This paper explores cloud deployment of chatbots systems and their performance assessment methodologies. The performance measures includes system response delays and natural language processing capabilities. A case study platform supporting so-called deep-logic chatbots with long cycling capabilities is implemented and used for the assessment. To enable human-like conversations with a chatbot, huge training data, complex natural language understanding models are required and need to be adjusted and trained continuously. We explore implementation formats supporting auto scaling, and uninterrupted availability. In particular, we employ an architecture consisting of separate dialog management, authentication, and Natural Language Understanding (NLU) services. Finally, we present a performance evaluation of such loosely coupled chatbot system. Keywords: Cloud Deployment, Natural language understanding, Chatbot, Performance assessment
This paper presents a status report on reader and adopter responses to printed interactive books using Ricoh’s Clickable Paper application. The paper describes how Ricoh’s Clickable Paper app has taken a major step forward with the growth of adoptions of the first book, Introduction to Graphic Communication, the completion of a second book, The Sound of Bamboo, and a third book in process focused on Black history and African American journeys to success. The diversity of these topics shows how Ricoh’s Clickable Paper technology is applicable for interdisciplinary fields such as graphic communication, the performing arts, and the social sciences._x005F_x000D_ _x005F_x000D_ A survey was taken of user and adopter reactions to the Clickable Paper application, with the major emphasis on the first book, Introduction to Graphic Communication, because it has entered its third year of use with adoptions to date by twenty-four schools. The second book, The Sound of Bamboo, focusing on music, is in its first year of adoption. Reviews to date are included. The third book is presently being written and scheduled for release in 2022. _x005F_x000D_ _x005F_x000D_ Content Analysis is the research method used to quantify the qualitative responses received. Therefore, all readers can interpret the results in the same way. _x005F_x000D_ _x005F_x000D_ In sum, the results are highly positive from students, schools, faculty members, and other readers of the Clickable Paper books. The scanning abilities of the Clickable Paper app received the greatest number of positive responses along with the value of the videos, and how the interactive Introduction to Graphic Communication book served an important need during the COVID-19 pandemic. Recommendations, for the most part, were not related to functionality of the Clickable Paper technology, but to cosmetic considerations and operational inconsistencies that some users experienced. The Clickable Paper app design received the greatest number of recommendations for improvement, followed by some discomfort in viewing images on the small screen size of smartphones. Remedies are provided.