Society seen through the prism of space: outline of a theory of society and space

Two questions challenge the student of space and society above all others: will new technologies change the spatial basis of society ? And if so, will this have an impact on society itself ? For the urbanist, these two questions crystallise into one: what will the future of cities have to do with their past ? Too often these questions are dealt with as though they were only matters of technology. But they are much more than that. They are deep and difficult questions about the interdependence of technology, space and society that we do not yet have the theoretical apparatus to answer. We know that previous �revolutions� in technology such as agriculture, urbanism and industrialisation associated radical changes in space with no less radical changes in social institutions. But we do not know how far these linkages were contingent or necessary. We do not, in short, have a theory of society and space adequate to account for where we are now, and therefore we have no reasonable theoretical base for speculating about the future. In this paper, I suggest that a major reason for this theoretical deficit is that most previous attempts to build a theory of society and space have looked at society and tried to find space in its output. The result has been that the constructive role of space in creating and and sustaining society has not been brought to the fore, or if it has, only in a way which is too general to permit the detailed specification of mechanisms. In this paper I try to reverse the normal order of things this by looking first at space and trying the discern society through space: by looking at society through the prism of space. Through this I try to define key mechanisms linking space to society and then use these to suggest how the questions about the future of cities and societies might be better defined

Interaction-based Human Activity Comparison

Traditional methods for motion comparison consider features from individual characters. However, the semantic meaning of many human activities is usually defined by the interaction between them, such as a high-five interaction of two characters. There is little success in adapting interaction-based features in activity comparison, as they either do not have a fixed topology or are in high dimensional. In this paper, we propose a unified framework for activity comparison from the interaction point of view. Our new metric evaluates the similarity of interaction by adapting the Earth Mover’s Distance onto a customized geometric mesh structure that represents spatial-temporal interactions. This allows us to compare different classes of interactions and discover their intrinsic semantic similarity. We created five interaction databases of different natures, covering both two characters (synthetic and real-people) and character-object interactions, which are open for public uses. We demonstrate how the proposed metric aligns well with the semantic meaning of the interaction. We also apply the metric in interaction retrieval and show how it outperforms existing ones. The proposed method can be used for unsupervised activity detection in monitoring systems and activity retrieval in smart animation systems

Indexing 3D scenes using the interaction bisector surface

The spatial relationship between different objects plays an important role in defining the context of scenes. Most previous 3D classification and retrieval methods take into account either the individual geometry of the objects or simple relationships between them such as the contacts or adjacencies. In this article we propose a new method for the classification and retrieval of 3D objects based on the Interaction Bisector Surface (IBS), a subset of the Voronoi diagram defined between objects. The IBS is a sophisticated representation that describes topological relationships such as whether an object is wrapped in, linked to, or tangled with others, as well as geometric relationships such as the distance between objects. We propose a hierarchical framework to index scenes by examining both the topological structure and the geometric attributes of the IBS. The topology-based indexing can compare spatial relations without being severely affected by local geometric details of the object. Geometric attributes can also be applied in comparing the precise way in which the objects are interacting with one another. Experimental results show that our method is effective at relationship classification and content-based relationship retrieval

Topology-based character motion synthesis

This thesis tackles the problem of automatically synthesizing motions of close-character interactions which appear in animations of wrestling and dancing. Designing such motions is a daunting task even for experienced animators as the close contacts between the characters can easily result in collisions or penetrations of the body segments. The main problem lies in the conventional representation of the character states that is based on the joint angles or the joint positions. As the relationships between the body segments are not encoded in such a representation, the path-planning for valid motions to switch from one posture to another requires intense random sampling and collision detection in the state-space. In order to tackle this problem, we consider to represent the status of the characters using the spatial relationship of the characters. Describing the scene using the spatial relationships can ease users and animators to analyze the scene and synthesize close interactions of characters. We first propose a method to encode the relationship of the body segments by using the Gauss Linking Integral (GLI), which is a value that specifies how much the body segments are winded around each other. We present how it can be applied for content-based retrieval of motion data of close interactions, and also for synthesis of close character interactions. Next, we propose a representation called Interaction Mesh, which is a volumetric mesh composed of points located at the joint position of the characters and vertices of the environment. This raw representation is more general compared to the tangle-based representation as it can describe interactions that do not involve any tangling nor contacts. We describe how it can be applied for motion editing and retargeting of close character interaction while avoiding penetration and pass-throughs of the body segments. The application of our research is not limited to computer animation but also to robotics, where making robots conduct complex tasks such as tangling, wrapping, holding and knotting are essential to let them assist humans for the daily life