Abstract
Social media and collection of large volumes of multimedia data such as images, videos and the accompanying text is of prime importance in today’s society. This is stimulated by the power of the humans to communicate one with the others. A useful paradigm of exploitation of such a huge amount of multimedia volumes is the 3D reconstruction and modelling of sites, historical cultural cities/regions or objects of interest from the short videos captured by simple users mainly for personal or touristic purposes. The main challenge in this research is the unstructured nature of the videos and the fact that they contain many information which is not related with the object the 3D model we ask for but for personal usage such as humans in front of the objects, weather conditions, etc. In this article, we propose an automatic scheme for 3D modelling/reconstruction of objects of interest by collecting pools of short duration videos that have been captured mainly for touristic purposes. Initially a video summarization algorithm is introduced using a discriminant Principal Component Analysis (d-PCA). The goal of this innovative scheme is to extract the frames so that bunches within each video cluster that contains videos of content referring to the same object present the maximum coherency of image data while content across bunches the minimum one. Experimental results on cultural objects indicate the efficiency pf the proposed method to 3D reconstruct assets of interest using an unstructured image content information. □
Highlights
Walking in the second decade of 21st century more and more people realize the impact of multimedia and social media in their lives
As stated by Ntalianis and Doulamis in (Ntalianis and Doulamis, 2016), the rich media content of the social media can be exploited to create personalized summaries of a human life making him/her “digitally perpetual” and leaving his/her mark in the world forever! This means in other words that we can create an album of our activities and lives in space and time which can be used as an historic mark of our family and friends’ tree for our descendants to come
We propose a novel video summarization scheme that is based on a discriminant Principal Component Analysis (d-PCA) as presented in the very recent work in (Wang et al, 2018)
Summary
Walking in the second decade of 21st century more and more people realize the impact of multimedia and social media in their lives. This, in sequel, has boosted the amount, the complexity and the diversity of the digital media being captured, generated, processed, analyzed, and stored across heterogeneous and distributed media repositories and cloud infrastructures such as Picasa, and Flickr (Sevillano et al, 2012). This huge amount of multimedia content, which forms the so-called User Generated Content (UGC) (Li et al, 2018), can be exploited toward a better human-to-human interaction and for a variety of new application domains in the broad fields of tourism, culture, leisure and entertainment (Kosmopoulos et al, 2009; Kim et al, 2014; Vishnevskaya et al, 2015). These issues are out of the scope of this paper but in our case, only freely available data are taken into account
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