247 research outputs found

    The Creation of Dynamic Visual Objects as a Factor for Optimizing Advertisements in E-Commerce

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    Introduction: The Covid-19 pandemic has boosted the development of online retail and has created an urgent need to transform digital marketing tools. The purpose of the study is to find ways to optimize advertising in Google and Facebook, which are the superior digital advertising platforms as their top digital advertising platforms in terms of both usage and performance.Methods: An experiment conducted as part of the study showed that the use of the dynamic optimization tool allows you to enrich existing feed data with additional 1st and 3rd party data and automatically compile visuals with additional information obtained from the feed and additional graphical overlays. The proposed method was tested on Facebook and Google with an analysis of click through rate, conversion rate and conversion cost indicators.Findings: The research results showed that the use of the dynamic optimization tool improves the effectiveness of online advertising, all the studied indicators has improved on both platforms. The results obtained complement to the few literature sources devoted to creating enriched feeds on various internet companies, so the work is of significant interest for marketers and business owners who work in the field of e-commerce. Originality: It has been established that in order to increase the conversion rates of ad campaigns and improve the quality of communication with the audience, a deeper study of the behavioral characteristics of visitors of internet resources, as well as high-quality visual content of the ads, are required.

    Purchasing behavior of professional buyers in out of home industry : The significance of price in the purchasing behavior

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    This research is observing purchasing behavior of professional buyers in the media industry. The study focuses on media agency personnel who are specialized in out of home advertis-ing. The research is conducted in three countries via online survey. The countries being Fin-land, Sweden, and United Kingdom. The key concepts of the thesis are out of home advertis-ing, cross cultural theory, media agencies, relationship marketing and purchasing behavior of professional buyers. Purchasing is important for companies because it has effect on the bottom line. Purchasing forms considerable portion of the turnover in most organizations. Outsourcing the purchases has become more common and it is expected to increase in the future. One of the most im-portant tasks of media agencies is to purchase media for their customers cost effectively. They create significant cost advantages and can increase the profitability of their clients. Me-dia agencies are seemed as crucial partners in the purchasing of media. The analysis of the study is conducted with quantitative analysis where the focus is on the relationship between four independent factors and the dependent factor. The four inde-pendent factors of organizational buying behavior are environmental force, organizational force, group force and individual force. The dependent factor is the importance of price in purchasing. These relationships are analyzed and whether they have significant influence. Then the relationships are moderated with masculinity dimension. Masculinity is a dimension from a model by Hofstede (1980) where he observed cross cultural theory from the perspec-tive of four different dimensions. The study has two objectives. The first concerns delivering data regarding purchasing behav-ior of professional buyers in the media industry and the second one gives an answer whether the masculinity dimension has effect on the purchasing behavior.Tässä työssä tutkitaan media-alan ammattiostajien ostokäyttäytymistä. Tutkimus keskittyy mediatoimistojen henkilökuntaan ja vielä tarkemmin niihin henkilöihin, jotka ovat ulkomai-nosalaan erikoistuneita. Työ toteutetaan kolmessa markkinassa verkkolomakkeen avulla. Nämä kolme maata ovat Yhdistyneet kuningaskunnat, Suomi ja Ruotsi. Työn pääaiheita ovat ulkomainonta, kulttuurien väliset teoriat, mediatoimistot, suhdemarkkinointi ja ammattiosta-jien ostokäyttäytyminen. Ostot ovat tärkeitä yrityksille, koska niillä on suora vaikutus yritysten tulokseen. Ostot vaikut-tavat merkittävästi yritysten liikevaihtoon. Ostojen ulkoistaminen on yleistynyt ja sen odote-taan kasvavan entisestään tulevaisuudessa. Yksi tärkeimmistä mediatoimistojen tehtävistä on ostaa mediaa heidän asiakkailleen kustannustehokkaasti. Mediatoimistot luovat merkittä-viä hintaetuja ja voivat kasvattaa näin asiakkaidensa kannattavuutta. Mediatoimistoja pide-tään tärkeinä kumppaneina median ostamisessa. Tutkimuksen analysointi toteutetaan kvantitatiivisella analyysillä, joka keskittyy neljään riip-pumattomaan tekijään ja yhteen riippuvaan tekijään. Nämä neljä riippumatonta tekijää ovat ympäristön vaikutus, organisaation vaikutus, ryhmän vaikutus ja yksilön vaikutus. Tutkimuk-sen riippuva tekijä on hinnan merkitys ostamisessa. Näiden neljän riippumattoman muuttu-jan suhdetta tutkitaan ja määritetään, onko niillä merkittävää vaikutusta hinnan merkityk-seen. Tämän jälkeen suhteita arvioidaan maskuliinisuuden avulla ja lisääkö maskuliinisuus hinnan merkitystä ostamisessa. Maskuliinisuus on yksi Hofstede:n (1980) luoman mallin nel-jästä tutkittavasta osa-alueesta. Kyseinen tutkimus tarkasteli kulttuurien välisiä eroja kansalli-sessa mittakaavassa. Tutkielmalla on kaksi tavoitetta. Ensimmäinen liittyy tietoon ammattiostajien ostopäätöksistä media-alalla ja toinen tutkimuskysymys vastaa miten maskuliinisuus vaikuttaa ostokäyttäy-tymiseen

    Structural failure analysis of Calumet Harbor breakwater

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    The advertising effects of connected television and digital out of home media : a field experiment

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    Television advertising has traditionally been used by marketers to reach mass audiences, but linear TV viewership is in decline as viewer attention moves toward emerging digital media. This fragmentation of audiences poses a challenge for marketing practitioners, who must learn which alternative media should be used in marketing plans to reach desired consumers. The aim of this research is to provide insights to marketing practitioners exploring new ways to communicate with fragmented audiences due to decreased linear TV viewership. The integrated marketing communications (IMC) paradigm presents one approach to exploring the individual and combined effects of media activated in an advertising campaign. However, there is limited information about the advertising effects of emerging media. As such, connected TV (CTV) and digital out of home (DOOH) have been selected to test the effectiveness of two emerging media. A critical literature review develops a conceptual model in accordance with the IMC paradigm and formulates six hypotheses to test the direct effect of attitude toward media on attitudinal outcomes of attitude toward the ad and brand opinion, and consumer decision outcomes of brand awareness, brand consideration, purchase intent and ad recall. In accordance with a positivist ontology, a field experiment is run for goodr, a nascent sports sunglasses brand seeking to add media beyond search and social media advertising to reach new customers. Using a GDPR-compliant mobile-based survey platform, a panel of 400 consumers is divided into four treatment groups of 100 people each: unexposed, exposed to CTV only, exposed to DOOH only and exposed to both CTV and DOOH. Linear and logistic regression analyses are used to assess the correlation between attitude to media and the dependent variables. Statistically significant positive relationships are identified for most hypotheses and Hayes Process analyses show statistically significant indirect relationships with attitude toward the ad as the mediator variable. Despite the supported hypotheses, the results demonstrate the challenge of measuring IMC activity given that evidence of media synergies is inconclusive. However, for a new business seeking to grow market share, the results show CTV and DOOH are effective and should be considered for media plans. The research provides a foundation for future research by identifying the need to consider a laboratory element in the methodology and use a video-based DOOH creative treatment to compare the medium with CTV more equally

    Eye center localization and gaze gesture recognition for human-computer interaction

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    © 2016 Optical Society of America. This paper introduces an unsupervised modular approach for accurate and real-time eye center localization in images and videos, thus allowing a coarse-to-fine, global-to-regional scheme. The trajectories of eye centers in consecutive frames, i.e., gaze gestures, are further analyzed, recognized, and employed to boost the human-computer interaction (HCI) experience. This modular approach makes use of isophote and gradient features to estimate the eye center locations. A selective oriented gradient filter has been specifically designed to remove strong gradients from eyebrows, eye corners, and shadows, which sabotage most eye center localization methods. A real-world implementation utilizing these algorithms has been designed in the form of an interactive advertising billboard to demonstrate the effectiveness of our method for HCI. The eye center localization algorithm has been compared with 10 other algorithms on the BioID database and six other algorithms on the GI4E database. It outperforms all the other algorithms in comparison in terms of localization accuracy. Further tests on the extended Yale Face Database b and self-collected data have proved this algorithm to be robust against moderate head poses and poor illumination conditions. The interactive advertising billboard has manifested outstanding usability and effectiveness in our tests and shows great potential for benefiting a wide range of real-world HCI applications

    2D and 3D computer vision analysis of gaze, gender and age

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    Human-Computer Interaction (HCI) has been an active research area for over four decades. Research studies and commercial designs in this area have been largely facilitated by the visual modality which brings diversified functionality and improved usability to HCI interfaces by employing various computer vision techniques. This thesis explores a number of facial cues, such as gender, age and gaze, by performing 2D and 3D based computer vision analysis. The ultimate aim is to create a natural HCI strategy that can fulfil user expectations, augment user satisfaction and enrich user experience by understanding user characteristics and behaviours. To this end, salient features have been extracted and analysed from 2D and 3D face representations; 3D reconstruction algorithms and their compatible real-world imaging systems have been investigated; case study HCI systems have been designed to demonstrate the reliability, robustness, and applicability of the proposed method.More specifically, an unsupervised approach has been proposed to localise eye centres in images and videos accurately and efficiently. This is achieved by utilisation of two types of geometric features and eye models, complemented by an iris radius constraint and a selective oriented gradient filter specifically tailored to this modular scheme. This approach resolves challenges such as interfering facial edges, undesirable illumination conditions, head poses, and the presence of facial accessories and makeup. Tested on 3 publicly available databases (the BioID database, the GI4E database and the extended Yale Face Database b), and a self-collected database, this method outperforms all the methods in comparison and thus proves to be highly accurate and robust. Based on this approach, a gaze gesture recognition algorithm has been designed to increase the interactivity of HCI systems by encoding eye saccades into a communication channel similar to the role of hand gestures. As well as analysing eye/gaze data that represent user behaviours and reveal user intentions, this thesis also investigates the automatic recognition of user demographics such as gender and age. The Fisher Vector encoding algorithm is employed to construct visual vocabularies as salient features for gender and age classification. Algorithm evaluations on three publicly available databases (the FERET database, the LFW database and the FRCVv2 database) demonstrate the superior performance of the proposed method in both laboratory and unconstrained environments. In order to achieve enhanced robustness, a two-source photometric stereo method has been introduced to recover surface normals such that more invariant 3D facia features become available that can further boost classification accuracy and robustness. A 2D+3D imaging system has been designed for construction of a self-collected dataset including 2D and 3D facial data. Experiments show that utilisation of 3D facial features can increase gender classification rate by up to 6% (based on the self-collected dataset), and can increase age classification rate by up to 12% (based on the Photoface database). Finally, two case study HCI systems, a gaze gesture based map browser and a directed advertising billboard, have been designed by adopting all the proposed algorithms as well as the fully compatible imaging system. Benefits from the proposed algorithms naturally ensure that the case study systems can possess high robustness to head pose variation and illumination variation; and can achieve excellent real-time performance. Overall, the proposed HCI strategy enabled by reliably recognised facial cues can serve to spawn a wide array of innovative systems and to bring HCI to a more natural and intelligent state

    Gender and gaze gesture recognition for human-computer interaction

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    © 2016 Elsevier Inc. The identification of visual cues in facial images has been widely explored in the broad area of computer vision. However theoretical analyses are often not transformed into widespread assistive Human-Computer Interaction (HCI) systems, due to factors such as inconsistent robustness, low efficiency, large computational expense or strong dependence on complex hardware. We present a novel gender recognition algorithm, a modular eye centre localisation approach and a gaze gesture recognition method, aiming to escalate the intelligence, adaptability and interactivity of HCI systems by combining demographic data (gender) and behavioural data (gaze) to enable development of a range of real-world assistive-technology applications. The gender recognition algorithm utilises Fisher Vectors as facial features which are encoded from low-level local features in facial images. We experimented with four types of low-level features: greyscale values, Local Binary Patterns (LBP), LBP histograms and Scale Invariant Feature Transform (SIFT). The corresponding Fisher Vectors were classified using a linear Support Vector Machine. The algorithm has been tested on the FERET database, the LFW database and the FRGCv2 database, yielding 97.7%, 92.5% and 96.7% accuracy respectively. The eye centre localisation algorithm has a modular approach, following a coarse-to-fine, global-to-regional scheme and utilising isophote and gradient features. A Selective Oriented Gradient filter has been specifically designed to detect and remove strong gradients from eyebrows, eye corners and self-shadows (which sabotage most eye centre localisation methods). The trajectories of the eye centres are then defined as gaze gestures for active HCI. The eye centre localisation algorithm has been compared with 10 other state-of-the-art algorithms with similar functionality and has outperformed them in terms of accuracy while maintaining excellent real-time performance. The above methods have been employed for development of a data recovery system that can be employed for implementation of advanced assistive technology tools. The high accuracy, reliability and real-time performance achieved for attention monitoring, gaze gesture control and recovery of demographic data, can enable the advanced human-robot interaction that is needed for developing systems that can provide assistance with everyday actions, thereby improving the quality of life for the elderly and/or disabled

    Evaluating detection limits of next-generation sequencing for the surveillance and monitoring of international marine pests

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    Most surveillance programmes for marine invasive species (MIS) require considerable taxonomic expertise, are laborious, and are unable to identify species at larval or juvenile stages. Therefore, marine pests may go undetected at the initial stages of incursions when population densities are low. In this study, we evaluated the ability of the benchtop GS Junior™ 454 pyrosequencing system to detect the presence of MIS in complex sample matrices. An initial in-silico evaluation of the mitochondrial cytochrome c oxidase subunit I (COI) and the nuclear small subunit ribosomal DNA (SSU) genes, found that multiple primer sets (targeting a ca. 400 base pair region) would be required to obtain species level identification within the COI gene. In contrast a single universal primer set was designed to target the V1–V3 region of SSU, allowing simultaneous PCR amplification of a wide taxonomic range of MIS. To evaluate the limits of detection of this method, artificial contrived communities (10 species from 5 taxonomic groups) were created using varying concentrations of known DNA samples and PCR products. Environmental samples (water and sediment) spiked with one or five 160 hr old Asterias amurensis larvae were also examined. Pyrosequencing was able to recover DNA/PCR products of individual species present at greater than 0.64% abundance from all tested contrived communities. Additionally, single A. amurensis larvae were detected from both water and sediment samples despite the co-occurrence of a large array of environmental eukaryotes, indicating an equivalent sensitivity to quantitative PCR. NGS technology has tremendous potential for the early detection of marine invasive species worldwide

    The Red Carpet Experience A video based spatial augmented reality platform

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    This research investigates screen based public space experiences that require little to no verbal or written instructions. The purpose of the research was rooted in observations and experiences developing screen based interactive and reactive public space installations for commercial use in the fields of marketing and advertising. The research initiated with an experimental prototype called “Walk The Red Carpet”, which evolved through experimentation into a platform for video based spatial augmented reality (SAR) experiences. Using the research approach of reflective practice, the first prototype was followed by a review of applicable concepts in the field of human computer interaction (HCI) and related social and cognitive psychology. The findings of this research, which are summarized and the conclusion of this work, is that video based SAR that effectively embodies the user’s form in the experience requires little or no written or verbal instructions in order for users to engage
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