Désormais, l'analyse des scènes denses s'impose incontestablement comme une tâche importante pour contrôler et gérer les foules. Notre recherche a pour objectifs d'apporter des solutions à l'estimation de la densité de la foule et de prouver l'utilité de cette estimation comme préalable pour d'autres applications. Concernant le premier objectif, afin de cerner les difficultés de la détection de personnes dans une foule, on se focalise sur l'estimation de la densité basée sur un niveau d'analyse bas. Dans un premier temps, on démontre que nos approches sont plus adéquates que les méthodes de l’état de l’art que ce soit pour compter les individus ou pour estimer le niveau de la foule. Dans un second temps, nous proposons une approche innovante dans laquelle une estimation locale au niveau des pixels remplace l'estimation au niveau global de la foule ou le nombre des personnes. Elle est basée sur l’utilisation des suivis de caractéristiques visuelles dans une fonction de densité. Notre recherche a également pour objectif d'utiliser la densité comme information supplémentaire pour affiner d'autres tâches. D'abord, nous avons utilisé la mesure de la densité qui comporte une description pertinente à la répartition spatiale des individus afin d'améliorer leur détection et leur suivi dans les foules. Ensuite, en prenant en compte la notion de la protection de la vie privée, nous ajustons le niveau de floutage en fonction de la densité de la foule. Enfin, nous nous appuyons sur l’estimation locale de la densité ainsi que sur le mouvement en tant qu'attributs pour des applications de haut niveau telles que la détection des évolutions et la reconnaissance des événements. / Crowd analysis has recently emerged as an increasingly important problem for crowd monitoring and management in the visual surveillance community. In this thesis, our objectives are to address the problems of crowd density estimation and to investigate the usefulness of such estimation as additional information to other applications. Towards the first goal, we focus on the problems related to the estimation of the crowd density using low level features in order to avert typical problems in detection of high density crowd. We demonstrate in this dissertation, that the proposed approaches perform better than the baseline methods, either for counting people, or alternatively for estimating the crowd level. Afterwards, we propose a novel approach, in which local information at the pixel level substitutes the overall crowd level or person count. It is based on modeling time-varying dynamics of the crowd density using sparse feature tracks as observations of a probabilistic density function. The second goal is to use crowd density as additional information to complement other tasks related to video surveillance in crowds. First, we use the proposed crowd density measure which conveys rich information about the local distributions of persons to improve human detection and tracking in videos of high density crowds. Second, we investigate the concept of crowd context-aware privacy protection by adjusting the obfuscation level according to the crowd density. Finally, we employ additional information about the local density together with regular motion patterns as crowd attributes for high level applications such as crowd change detection and event recognition.

This thesis investigates variation in human cooperative behaviour in naturally occurring contexts. I critically assess the prevailing consensus on human cooperation derived from laboratory games (such as the dictator and public goods games), by identifying real life analogues and conducting extensive field observation and experiments. My second chapter investigates the importance of context on social behaviour by taking a commonly used laboratory game, the dictator game, and studying analogous behaviour, giving to mendicants in the street. I conclude that individuals cooperate less in the wild than they do in the laboratory and that monetary pay-offs are important in cooperative decision-making. My third chapter examines how social cues influence peoples' likelihood of giving to mendicants. I conclude that increased group size and crowd density negatively affect donation behaviour. My fourth chapter investigates dog fouling in public parks to understand the causes of variation in cheating in a naturally occurring public goods game. I conclude that despite evidence that a social game is being played, the cues that influences decisions are unclear, and behaviour may depend on local social norms. My fifth chapter investigates social influences on red light jumping by cyclists at pedestrian crossings. I find that the probability of cheating is higher with fewer observers and when other cyclists also cheat.

This study investigates how people's perceived sense of safety affects their use of and feeling of safety when they are in a park. The chosen location for the case study research is Karlstad City Garden. Currently, Karlstad City Garden is underutilized and was described as unsafe in a survey conducted by the municipality of Karlstad in 2018 (Karlstad kommun 2019). The purpose of this study is to examine visitors' perceived feelings of safety when they are in Karlstad City Garden. The study will focus on four factors; lighting, lack of people, maintenance, and visibility to provide what effect they have on people when they visit a public place. Previous research, including the municipality's safety survey, identified these four factors as significant contributors to visitors' feelings of safety. This study aims to gain a better understanding of why visitors perceive themselves as safe or unsafe in the park and how these four factors influence their perceived sense of safety. To investigate visitors' experiences of the park, a questionnaire was distributed through social media, and QR codes were distributed in the park to reach a diverse range of respondents. Additionally, observations were conducted as part of the study, primarily to complement the questionnaire and strengthen the findings. The study findings revealed that the time of day and the four factors mentioned above influenced visitors' perceived sense of safety in the park. During the day, more people were present, which made visitors feel safer. In the evening, the park was largely empty, and there were few visitors. The feelings of safety during this time could be attributed to the low population in the park, inadequate lighting in most areas, and reduced visibility during the evening. The poor visibility and lighting could be a result of insufficient maintenance, particularly in the densely vegetated southern part of the park. As a result, many people may have avoided visiting the park in the evening due to feeling unsafe.