Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

Vision Modulates Corticospinal Suppression in a Functionally Specific Manner during Movement of the Opposite Limb

The effect of vision on the excitability of corticospinal projections to the flexor carpi radialis (FCR) and extensor carpi radialis (ECR) muscles of right human forearm was investigated before and during discrete movement of the opposite limb. An external force opposed the initial phase of the movement (wrist flexion) and assisted the reverse phase, so that recruitment of the wrist extensors was minimized. Three conditions were used as follows: viewing the inactive right limb (Vision), viewing the mirror image of the moving left limb (Mirror), and with vision of the right limb occluded (No Vision). Transcranial magnetic stimulation was delivered to the left motor cortex: before, at the onset of, or during the left limb movement to obtain motor evoked potentials (MEPs) in the muscles of the right forearm. At and following movement onset, MEPs obtained in the right FCR were smaller in the Vision condition than in the Mirror and No Vision conditions. A distinct pattern of variation was obtained for the ECR. In all conditions, MEPs in this muscle were elevated upon or following movement of the opposite limb. An additional analysis of ipsilateral silent periods indicated that interhemispheric inhibition plays a role in mediating these effects. Activity-dependent changes in corticospinal output to a resting limb during discrete actions of the opposite limb are thus directly contingent upon where one looks. Furthermore, the extent to which vision exerts an influence upon projections to specific muscles varies in accordance with the functional contribution of their homologs to the intended action.

Vision and Virtuality:The Construction of Narrative Space in Film and Computer Games

This paper seeks to explore the construction of narrative space in 3D PC computer games. With reference to Stephen Heath’s theory of filmic narrative space, the paper will examine how computer games, based on the rendition of a continuous 3D, real-time interactive environment, construct a distinct mode of narrativisation. The dynamic imbrication of the manipulation of 3D objects in a virtual world and the (re)presentation of this virtual mise-en-scene constitute an interaction that affects the concept of narrative in computer games. This leads to several questions that the paper seeks to investigate: How does the construction of space in PC games contribute to the meaning-making process or the gamer’s experience of narrative? How then is this experience of narrative game-space different from that of film?

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.