MM

Founded in May 2009, Microworkers.com is an international Crowdsourcing platform focusing on Microtasks. At present, more than 600,000 users from over 190 countries have already registered to our platform. This extensively diverse workforce is the key ...

Recently, we released a large affective video dataset, namely LIRIS-ACCEDE, which was annotated through crowdsourcing along both induced valence and arousal axes using pairwise comparisons. In this paper, we design an annotation protocol which enables ...

This paper attempts to model IA in personal photo collections through a user-centric perspective. To understand how users deemed an image as being more/less appealing, an extensive crowdsourcing experiment was conducted with 350 workers and five ...

We propose Multi-task learning (MTL) for time-continuous or dynamic emotion (valence and arousal) estimation in movie scenes. Since compiling annotated training data for dynamic emotion prediction is tedious, we employ crowdsourcing for the same. Even ...

Crowdsourcing has the potential to become a preferred tool to study image aesthetic appeal preferences of users. Nevertheless, some reliability issues still exist, partially due to the sometimes doubtful commitment of paid workers to perform the rating ...

In this paper, we introduce a scale for measuring the extrinsic motivation of crowd workers. The new questionnaire is strongly based on the Work Extrinsic Intrinsic Motivation Scale (WEIMS) [17] and theoretically follows the Self-Determination Theory (...

Crowdsourcing is popular in multimedia research to obtain image annotation and segmentation data at scale. In the context of analysis of cultural heritage materials, we propose a novel crowdsourced task, namely the segmentation of ancient Maya ...

In this paper we investigate whether and how the human choice of images for summarizing a visual collection is influenced by the semantic concepts depicted in them. More specifically, by analysing a large collection of human-created visual summaries ...

Research on mid-level image representations has conventionally concentrated relatively obvious attributes and overlooked non-obvious attributes, i.e., characteristics that are not readily observable when images are viewed independently of their context ...

We present a crowdsourcing approach to tackle the challenge of collecting hard-to-find data. Our immediate need for the data arises because we are studying edited images in context online, and the way that this use impacts users' perceptions. Study of ...

This paper introduces Click'n'Cut, a novel web tool for interactive object segmentation designed for crowdsourcing tasks. Click'n'Cut combines bounding boxes and clicks generated by workers to obtain accurate object segmentations. These segmentations ...

A timed tag is a tag that a user has assigned to a specific time point in a video. Although timed tags are supported by an increasing number of social video platforms on the Internet, multimedia research remains focused on conventional tags, here called ...

Recent developments in sport analytics have heightened the interest in collecting data on the behavior of individuals and of the entire team in sports events. Rather than using dedicated sensors for recording the data, the detection of semantic events ...

Validating user tags helps to refine them, making them more useful for finding images. In the case of interpretation-sensitive tags, however, automatic (i.e., pixel-based) approaches cannot be expected to deliver optimal results. Instead, human input is ...