Abstract
Machine Learning (ML) solutions are rapidly evolving and are increasingly capable of performing Automated Visual Data Processing (AVDP) tasks such as visual scene understanding, 3D model reconstruction and automated content generation tasks. We believe that novel AVDP solutions can significantly boost a company's business, streamline the creation of 3D content and models, enable adaptation of content in XR applications and support the creation of digital twins for a company's needs. However, there are also obstacles that limit the business use of such solutions. The objective of our research is to study the skills and insights of companies in using different kinds of AVDP solutions in their business. This article presents the results of interviews with 10 Finnish companies. The interviews comprised three sections: The first section gave a brief introduction about the existing AVDP solutions for the respondents. The second section collected information on the respondents' background and the respective company's experience of using ML in business and its short and long-term interest in developing or using different AVDP solutions in its business. The third section comprised thematic interviews which covered visual data processing themes that the respondents selected to be of interest to their company's business.
Highlights
Recent advances in Automated Visual Data Processing (AVDP) solutions such as Machine Learning (ML)-based visual scene understanding, 3D model reconstruction and automated content generation solutions can provide great business potential and a business ecosystem for companies that either develop or use these novel solutions in their business.In order to boost the use of novel AVDP solutions in business and to study the skills and insights of a company in using such solutions, we decided to interview companies that could benefit from such solutions and adopt different roles in an AVDP business ecosystem
The respondents believed that ML could be used at least to some extent for specific tasks in their business. 90% of the companies had experimented in using ML or had used ML in business and 30% of the companies already used ML in their business
The type and size of a company affects the expected role of the company in an AVDP ecosystem
Summary
Recent advances in Automated Visual Data Processing (AVDP) solutions such as ML-based visual scene understanding, 3D model reconstruction and automated content generation solutions can provide great business potential and a business ecosystem for companies that either develop or use these novel solutions in their business. In order to boost the use of novel AVDP solutions in business and to study the skills and insights of a company in using such solutions, we decided to interview companies that could benefit from such solutions and adopt different roles in an AVDP business ecosystem. The respondents answered general questions that covered their. The third section comprised thematic interviews which covered visual data processing themes that the respondents selected to be of interest to their company. We analysed the responses and prepared a summary showing the kind of AVDP solutions that the interviewed companies need
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