In current city visualisations crowds are being included to increase realism in the scene. With the self-steering nature of crowds it is traditionally difficult to control the number of humans that could be in view at any one time. While rendering speedups have been successfully applied for many years, this paper takes another approach with the aim to keep a steady frame rate. We attempt to inf...

We present a formal analysis technique for probabilistic security properties of peer-to-peer communication systems based on random message routing among members. The behavior of group members and the adversary is modeled as a discrete-time Markov chain, and security properties are expressed as PCTL formulas. To illustrate feasibility of the approach, we model the Crowds system for anonymous Web...

In knowledge-based economies, many businesses enterprises defy traditional industry boundaries. In this study, we evaluate six “big data” approaches to peer firm identifications and show that some, but not all, “wisdom-of-crowd” techniques perform exceptionally well. We propose an analytical framework for understanding when crowds can be expected to provide wisdom and show, theoretically and em...

INTRODUCTION Crowd computing like the crowd itself – builds on the idea that humanity is greater than the sum of its parts. With such roots, it is understandable how crowd computing has typically focused on finding common ground – mutual goals like improving teaching or audience understanding (Griswold, Rekimoto), communicating individually with audience members or simply making the variety of ...

Open innovation platforms (web sites where crowds post ideas in a shared space) enable us to elicit huge volumes of potentially valuable solutions for problems we care about, but identifying the best ideas in these collections can be prohibitively expensive and time-consuming. This paper presents an approach, called the "bag of lemons", which enables crowd to filter ideas with accuracy superior...

The animation and rendering of crowds of realistically clothed characters presents a difficult challenge in computer graphics, which is further exacerbated when real-time frame rates are required. To date, due to real-time constraints, standard skinning methods have been used to animate the clothes of individuals in real-time crowds, which does not create the appropriate secondary motion for fl...

In crowding, the perception of a target deteriorates in the presence of neighboring elements. Crowding is not a new research area but has fascinated researchers for centuries, dating back to 1738, as outlined in Strasburger and Wade (2015). The classic example of crowding is reading where the letters of a word mutually crowd each other. Thus, not surprisingly, crowding research has started off ...

On-line learning algorithms are particularly suitable for developing interactive computational agents. These algorithm can be used to teach the agents the abilities needed for engaging in social interactions with humans. If humans are used as teachers in the context of on-line learning algorithms a serious challenge arises: their lack of commitment and availability during the required extensive...

Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the state-of-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets. Recently, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of...

This study introduces a totally unsupervised method for the detection and location of dense crowds in images without context-awareness. With the perspective of setting up fully autonomous video-surveillance systems, automatic detection and location of crowds is a crucial step that is going to point which areas of the image have to be analyzed. After retrieving multiscale texturerelated feature ...