Action and non-action oriented body representations. insight from behavioural and grey matter modifications in individuals with lower limb amputation

Following current model of body representations, we aimed to systematically investigate the association between brain modifications, in terms of grey matter loss, and body representation deficits, in terms of alterations of the body schema (BS) and of non-action oriented body representations (NA), in individuals with lower limb amputation (LLA)

Evaluating a workspace's usefulness for image retrieval

Image searching is a creative process. We have proposed a novel image retrieval system that supports creative search sessions by allowing the user to organise their search results on a workspace. The workspace’s usefulness is evaluated in a task-oriented and user-centred comparative experiment, involving design professionals and several types of realistic search tasks. In particular, we focus on its effect on task conceptualisation and query formulation. A traditional relevance feedback system serves as a baseline. The results of this study show that the workspace is more useful in terms of both of the above aspects and that the proposed approach leads to a more effective and enjoyable search experience. This paper also highlights the influence of tasks on the users’ search and organisation strategy

Understanding customers' holistic perception of switches in automotive human–machine interfaces

For successful new product development, it is necessary to understand the customers' holistic experience of the product beyond traditional task completion, and acceptance measures. This paper describes research in which ninety-eight UK owners of luxury saloons assessed the feel of push-switches in five luxury saloon cars both in context (in-car) and out of context (on a bench). A combination of hedonic data (i.e. a measure of ‘liking’), qualitative data and semantic differential data was collected. It was found that customers are clearly able to differentiate between switches based on the degree of liking for the samples' perceived haptic qualities, and that the assessment environment had a statistically significant effect, but that it was not universal. A factor analysis has shown that perceived characteristics of switch haptics can be explained by three independent factors defined as ‘Image’, ‘Build Quality’, and ‘Clickiness’. Preliminary steps have also been taken towards identifying whether existing theoretical frameworks for user experience may be applicable to automotive human–machine interfaces

SpaceNet MVOI: a Multi-View Overhead Imagery Dataset

Detection and segmentation of objects in overheard imagery is a challenging task. The variable density, random orientation, small size, and instance-to-instance heterogeneity of objects in overhead imagery calls for approaches distinct from existing models designed for natural scene datasets. Though new overhead imagery datasets are being developed, they almost universally comprise a single view taken from directly overhead ("at nadir"), failing to address a critical variable: look angle. By contrast, views vary in real-world overhead imagery, particularly in dynamic scenarios such as natural disasters where first looks are often over 40 degrees off-nadir. This represents an important challenge to computer vision methods, as changing view angle adds distortions, alters resolution, and changes lighting. At present, the impact of these perturbations for algorithmic detection and segmentation of objects is untested. To address this problem, we present an open source Multi-View Overhead Imagery dataset, termed SpaceNet MVOI, with 27 unique looks from a broad range of viewing angles (-32.5 degrees to 54.0 degrees). Each of these images cover the same 665 square km geographic extent and are annotated with 126,747 building footprint labels, enabling direct assessment of the impact of viewpoint perturbation on model performance. We benchmark multiple leading segmentation and object detection models on: (1) building detection, (2) generalization to unseen viewing angles and resolutions, and (3) sensitivity of building footprint extraction to changes in resolution. We find that state of the art segmentation and object detection models struggle to identify buildings in off-nadir imagery and generalize poorly to unseen views, presenting an important benchmark to explore the broadly relevant challenge of detecting small, heterogeneous target objects in visually dynamic contexts.Comment: Accepted into IEEE International Conference on Computer Vision (ICCV) 201