Statistical Machine Learning for Human Behaviour Analysis

Human behaviour analysis has introduced several challenges in various fields, such as applied information theory, affective computing, robotics, biometrics and pattern recognition. This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue [1-15]. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field. Most of the included papers are application-based systems, while [15] focuses on the understanding and interpretation of a classification model, which is an important factor for the classifier's credibility. Given a set of categorical data, [15] utilizes multi-objective optimization algorithms, like ENORA and NSGA-II, to produce rule-based classification models that are easy to interpret. Performance of the classifier and its number of rules are optimized during the learning, where the first one is obviously expected to bemaximizedwhile the second one is expected to beminimized. Testing on public databases, using 10-fold cross-validation, shows the superiority of the proposed method against classifiers that are generated using other previously published methods like PART, JRip, OneR and ZeroR. Two published papers ([1,9]) have privacy as their main concern, while they develop their respective systems for biometrics recognition and action recognition. Reference [1] has considered a privacy-aware biometrics system. The idea is that the identity of the users should not be readily revealed from their biometrics, like facial images. Therefore, they have collected a database of foot and hand traits of users while opening a door to grant or deny access, while [9] develops a privacy-aware method for action recognition using recurrent neural networks. The system accumulates reflections of light pulses omitted by a laser, using a single-pixel hybrid photodetector. This includes information about the distance of the objects to the capturing device and their shapes

Animal-Computer Interaction: the emergence of a discipline

In this editorial to the IJHCS Special Issue on Animal-Computer Interaction (ACI), we provide an overview of the state-of-the-art in this emerging field, outlining the main scientific interests of its developing community, in a broader cultural context of evolving human-animal relations. We summarise the core aims proposed for the development of ACI as a discipline, discussing the challenges these pose and how ACI researchers are trying to address them. We then introduce the contributions to the Special Issue, showing how they illustrate some of the key issues that characterise the current state-of-the-art in ACI, and finally reflect on how the journey ahead towards developing an ACI discipline could be undertaken

Visual geographies : an editorial

The use of image-processing procedures and techniques and their products – photographs, aerial photographs, satellite images, maps – and the application of GIS and GPS, so-called "geomatics" (Thornes, 2004:787), are taken for granted in academic geographical practice today..

Editorial: Social inclusion

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Rhythm and synchrony in animal movement and communication

Animal communication and motoric behavior develop over time. Often, this temporal dimension has communicative relevance and is organized according to structural patterns. In other words, time is a crucial dimension for rhythm and synchrony in animal movement and communication. Rhythm is defined as temporal structure at a second-millisecond time scale (Kotz et al. 2018). Synchrony is defined as precise co-occurrence of 2 behaviors in time (Ravignani 2017). Rhythm, synchrony, and other forms of temporal interaction are taking center stage in animal behavior and communication. Several critical questions include, among others: what species show which rhythmic predispositions? How does a species’ sensitivity for, or proclivity towards, rhythm arise? What are the species-specific functions of rhythm and synchrony, and are there functional trends across species? How did similar or different rhythmic behaviors evolved in different species? This Special Column aims at collecting and contrasting research from different species, perceptual modalities, and empirical methods. The focus is on timing, rhythm and synchrony in the second-millisecond range. Three main approaches are commonly adopted to study animal rhythms, with a focus on: 1) spontaneous individual rhythm production, 2) group rhythms, or 3) synchronization experiments. I concisely introduce them below (see also Kotz et al. 2018; Ravignani et al. 2018)

Seeing the trees as well as the forest: the importance of managing forest genetic resources

Reliable data on the status and trends of forest genetic resources are essential for their sustainable management. The reviews presented in this special edition of Forest Ecology and Management on forest genetic resources complement the first ever synthesis of the State of the World’s Forest Genetic Resources (SOW-FGR) that has just been published by the Food and Agriculture Organization. In this editorial, we present some of the key findings of the SOW-FGR and introduce the seven reviews presented in this special edition on: (1) tree genetic resources and livelihoods; (2) the benefits and dangers of international germplasm transfers; (3) genetic indicators for monitoring threats to populations and the effectiveness of ameliorative actions; (4) the genetic impacts of timber management practices; (5) genetic considerations in forest ecosystem restoration projects using native trees; (6) genetic-level responses to climate change; and (7) ex situ conservation approaches and their integration with in situ methods. Recommendations for action arising from the SOW-FGR, which are captured in the first Global Plan of Action for the Conservation, Sustainable Use and Development of Forest Genetic Resources, and the above articles are discussed. These include: increasing the awareness of the importance of and threats to forest genetic resources and the mainstreaming of genetic considerations into forest management and restoration; establishing common garden provenance trials to support restoration and climate change initiatives that extend to currently little-researched tree species; streamlining processes for germplasm exchange internationally for research and development; and the intelligent use of modern molecular marker methods as genetic indicators in management and for improvement purposes

The Matter of Entrepreneurial Learning: A Literature Review

This paper is a comprehensive review of the entrepreneurial learning literature and its engagement with the material aspects of entrepreneurship, as part of the “material turn” in the social sciences. Drawing on actor-network theory, we construct a classificatory scheme and an evaluative matrix to find that this field is dominated by an anthropocentric bias and cognitivist approaches which largely ignore issues of materiality in entrepreneurship. However we also identify some heterogeneous network-based conceptualisations of entrepreneurial learning which could provide the foundations for more materially aware approaches. We conclude by calling for a material turn in entrepreneurial learning and outline some possible avenues for it

Quantitative assessment of intrinsic noise for visually guided behaviour in zebrafish

Supported by Royal Society of London (University Research Fellowship), Medical Research Council (New Investigator Research Grant) and CNRS.Peer reviewedPostprin