25,214 research outputs found
6 Seconds of Sound and Vision: Creativity in Micro-Videos
The notion of creativity, as opposed to related concepts such as beauty or
interestingness, has not been studied from the perspective of automatic
analysis of multimedia content. Meanwhile, short online videos shared on social
media platforms, or micro-videos, have arisen as a new medium for creative
expression. In this paper we study creative micro-videos in an effort to
understand the features that make a video creative, and to address the problem
of automatic detection of creative content. Defining creative videos as those
that are novel and have aesthetic value, we conduct a crowdsourcing experiment
to create a dataset of over 3,800 micro-videos labelled as creative and
non-creative. We propose a set of computational features that we map to the
components of our definition of creativity, and conduct an analysis to
determine which of these features correlate most with creative video. Finally,
we evaluate a supervised approach to automatically detect creative video, with
promising results, showing that it is necessary to model both aesthetic value
and novelty to achieve optimal classification accuracy.Comment: 8 pages, 1 figures, conference IEEE CVPR 201
Social Media Advertisement Outreach: Learning the Role of Aesthetics
Corporations spend millions of dollars on developing creative image-based
promotional content to advertise to their user-base on platforms like Twitter.
Our paper is an initial study, where we propose a novel method to evaluate and
improve outreach of promotional images from corporations on Twitter, based
purely on their describable aesthetic attributes. Existing works in aesthetic
based image analysis exclusively focus on the attributes of digital
photographs, and are not applicable to advertisements due to the influences of
inherent content and context based biases on outreach.
Our paper identifies broad categories of biases affecting such images,
describes a method for normalization to eliminate effects of those biases and
score images based on their outreach, and examines the effects of certain
handcrafted describable aesthetic features on image outreach. Optimizing on the
describable aesthetic features resulting from this research is a simple method
for corporations to complement their existing marketing strategy to gain
significant improvement in user engagement on social media for promotional
images.Comment: Accepted to SIGIR 201
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