Multichannel Attention Network for Analyzing Visual Behavior in Public Speaking

Public speaking is an important aspect of human communication and interaction. The majority of computational work on public speaking concentrates on analyzing the spoken content, and the verbal behavior of the speakers. While the success of public speaking largely depends on the content of the talk, and the verbal behavior, non-verbal (visual) cues, such as gestures and physical appearance also play a significant role. This paper investigates the importance of visual cues by estimating their contribution towards predicting the popularity of a public lecture. For this purpose, we constructed a large database of more than $1800$ TED talk videos. As a measure of popularity of the TED talks, we leverage the corresponding (online) viewers' ratings from YouTube. Visual cues related to facial and physical appearance, facial expressions, and pose variations are extracted from the video frames using convolutional neural network (CNN) models. Thereafter, an attention-based long short-term memory (LSTM) network is proposed to predict the video popularity from the sequence of visual features. The proposed network achieves state-of-the-art prediction accuracy indicating that visual cues alone contain highly predictive information about the popularity of a talk. Furthermore, our network learns a human-like attention mechanism, which is particularly useful for interpretability, i.e. how attention varies with time, and across different visual cues by indicating their relative importance

Plasticity facilitates sustainable growth in the commons

In the commons, communities whose growth depends on public goods, individuals often rely on surprisingly simple strategies, or heuristics, to decide whether to contribute to the common good (at risk of exploitation by free-riders). Although this appears a limitation, here we show how four heuristics lead to sustainable growth by exploiting specific environmental constraints. The two simplest ones --contribute permanently or switch stochastically between contributing or not-- are first shown to bring sustainability when the public good efficiently promotes growth. If efficiency declines and the commons is structured in small groups, the most effective strategy resides in contributing only when a majority of individuals are also contributors. In contrast, when group size becomes large, the most effective behavior follows a minimal-effort rule: contribute only when it is strictly necessary. Both plastic strategies are observed in natural systems what presents them as fundamental social motifs to successfully manage sustainability

Feature-based Choice and Similarity in Normal-form Games: An Experimental Study

In this paper, we test the effect of descriptive "features" on initial strategic behavior in normal form games, where the term "descriptive" indicates all those features which can be modified without altering the (Nash) equilibrium structure of a game. Our experimental subjects behaved according to some simple heuristics based on descriptive features, and we observed that these heuristics were stable even across strategically different games. These findings indicate the need to incorporate descriptive features into models describing strategic sophistication in normal form games. Analysis of choice patterns and individual behavior indicates that non-equilibrium choices may derive from incorrect and simplified mental representations of the game structure, rather than from beliefs in other players' irrationality. We suggest how level-k and cognitive hierarchy models might be extended to account for heuristic-based and feature-based behavior.normal form games, one-shot games, response times, dominance, similarity, categorization, focal points, individual behavior

The goal dependent automaticity of drinking habits

In recent treatments of habitual social behaviour, habits are conceptualised as a form of goal-directed automatic behaviour that are mentally represented as goal-action links. Three experiments tested this conceptualisation in the context of students’ drinking (alcohol consumption) habits. Participants were randomly assigned to conditions where either a goal related to drinking behaviour (socialising) was activated, or an unrelated goal was activated. In addition, participants’ drinking habits were measured. The dependent variable in Experiments 1 and 2 was readiness to drink, operationalised by speed of responding to the action concept “drinking” in a verb verification task. Experiment 3 used uptake of a voucher to measure drinking behaviour. Findings supported the view that when habits are established, simply activating a goal related to the focal behaviour automatically elicits that behaviour. These findings are consistent with a goal-dependent conception of habit. Possibilities for interventions designed to attenuate undesirable habitual behaviours are considered

Crowdsourcing in Computer Vision

Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of visual perception tasks. In this survey, we describe the types of annotations computer vision researchers have collected using crowdsourcing, and how they have ensured that this data is of high quality while annotation effort is minimized. We begin by discussing data collection on both classic (e.g., object recognition) and recent (e.g., visual story-telling) vision tasks. We then summarize key design decisions for creating effective data collection interfaces and workflows, and present strategies for intelligently selecting the most important data instances to annotate. Finally, we conclude with some thoughts on the future of crowdsourcing in computer vision.Comment: A 69-page meta review of the field, Foundations and Trends in Computer Graphics and Vision, 201

Gendering, courtship and pay equality: developing attraction theory to understand work-life balance and entrepreneurial activity

Objectives: This paper examines one of the most intractable problems of the last 40 years: the difficulty in closing the pay inequality gap. Current wisdom is that the pay gap exists because of men's power to control the workplace, and men's dominant position in society generally. This paper examines an emergent literature on matriarchal power structures and proposes Attraction Theory as a holistic framework. Prior Work: This paper acknowledges a range of feminist literature that examines the underlying social relations and power structures that impact on pay differentials. This is critiqued on the basis of findings from courtship research as well as studies emerging from liberal / progressive writers in the men's movement. Approach: This paper is conceptual, using an inter-disciplinary understanding of social processes to critically appraise both the dominant discourse on equal pay and its emergent alternative. Attraction Theory is presented as a framework for exploring a complex discourse that unequal pay exists both because of men's power to control the workplace and women's power to control courtship and family life. Implications: Tackling pay inequality and work-life balance issues by focussing on power sharing in the workplace represents only a partial policy solution. Further progress depends on power-sharing in parental rights through academic recognition and political action to tackle negative stereotypes that impact on men during romantic courtship, conception, birth and divorce. Value: The value of the paper lies in the originality of the analysis and the range of insights that Attraction Theory provides into societal dynamics that impact on equal pay. The identification of paradoxes in the dominant discourse opens up new avenues for research and policy development on work-life balance. Whether these will close the pay gap is unclear, but it would advance equality and diversity goals by creating confidence that consensual choices rather the institutional inequalities perpetuate any remaining inequalities reported in statistics.</p