Towards a taxonomy of movement patterns

Abstract

A review of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement patterns and only few, isolated definitions of these exist. Since the research interest in this area has recently started to soar, we believe that this is a good time to approach the definition of movement patterns in a more systematic and comprehensive way. This paper intends to contribute to the development of a toolbox of data mining algorithms and visual analytic techniques for movement analysis by developing firstly a conceptual framework for movement behavior of different moving objects and secondly a comprehensive classification and review of movement patterns. We argue that this is indispensable as a basis for the development of pattern recognition and information visualization algorithms that are required to be efficient (i.e. usable on massive data sets), effective (i.e. capable of accurately detecting patterns not artifacts), and as generic as possible (i.e. potentially applicable to different types of movement data). We demonstrate the utilization of our classification by answering the question as to what extent eye tracking data can be seen as a proxy of other types of movement data. We have set up a moderated discussion platform in order to facilitate the further evolution of our proposed classification towards a consolidated taxonomy in a consensus process.

Context‐aware movement analytics: implications, taxonomy, and design framework

“…47 However, a similar type of context information can be labeled both primary and secondary. Dodge et al 62 also classified the derivative (secondary) parameters into primary and secondary derivatives. That is, secondary derivatives are functions of primary derivatives, and primary derivatives are functions of primary contexts.…”

“…Movement context refers to the entities' quantitative parameters (e.g., speed and acceleration) that are generated as the movement commences. Spaccapietra et al 73 termed these parameters movement characteristics whereas Dodge et al 62 called such descriptors primary and secondary parameters. Hereafter, we refer to these dynamic physical descriptors as movement context.…”

Understanding movement data quality

“…For example, a pertinent property of eye movement is the presence of instantaneous jumps (saccades) over relatively long distances (Dodge et al 2008(Dodge et al , 2009. Intermediate points between start and end positions of a saccade are not meaningful: it cannot be assumed that there exists a straight or curved line between two fixation positions such that the eye focus travels along it attending all intermediate points.…”

Conflict in Pedestrian Networks

“…Considering a large number of entities at the level of the collectives instead of the level of the individuals can also be computationally more efficient. Pedestrians can be grouped according to their travel purposes [8], origin and destination points [9], or shared movement characteristics [6,10]. This paper compares the proposed method when considering random flows versus collective motion of the network.…”