Data-Efficient Decentralized Visual SLAM

Decentralized visual simultaneous localization and mapping (SLAM) is a powerful tool for multi-robot applications in environments where absolute positioning systems are not available. Being visual, it relies on cameras, cheap, lightweight and versatile sensors, and being decentralized, it does not rely on communication to a central ground station. In this work, we integrate state-of-the-art decentralized SLAM components into a new, complete decentralized visual SLAM system. To allow for data association and co-optimization, existing decentralized visual SLAM systems regularly exchange the full map data between all robots, incurring large data transfers at a complexity that scales quadratically with the robot count. In contrast, our method performs efficient data association in two stages: in the first stage a compact full-image descriptor is deterministically sent to only one robot. In the second stage, which is only executed if the first stage succeeded, the data required for relative pose estimation is sent, again to only one robot. Thus, data association scales linearly with the robot count and uses highly compact place representations. For optimization, a state-of-the-art decentralized pose-graph optimization method is used. It exchanges a minimum amount of data which is linear with trajectory overlap. We characterize the resulting system and identify bottlenecks in its components. The system is evaluated on publicly available data and we provide open access to the code.Comment: 8 pages, submitted to ICRA 201

Visual analysis of document triage data

As part of the information seeking process, a large amount of effort is invested in order to study and understand how information seekers search through documents such that they can assess their relevance. This search and assessment of document relevance, known as document triage, is an important information seeking process, but is not yet well understood. Human-computer interaction (HCI) and digital library scientists have undertaken a series of user studies involving information seeking, collected a large amount of data describing information seekers' behavior during document search. Next to this, we have witnessed a rapid increase in the number of off-the-shelf visualization tools which can benefit document triage study. Here we set out to utilize existing information visualization techniques and tools in order to gain a better understanding of the large amount of user-study data collected by HCI and digital library researchers. We describe the range of available tools and visualizations we use in order to increase our knowledge of document triage. Treemap, parallel coordinates, stack graph, matrix chart, as well as other visualization methods, prove to be insightful in exploring, analyzing and presenting user behavior during document triage. Our findings and visualizations are evaluated by HCI and digital library researchers studying this proble

Visual and interactive exploration of point data

Point data, such as Unit Postcodes (UPC), can provide very detailed information at fine scales of resolution. For instance, socio-economic attributes are commonly assigned to UPC. Hence, they can be represented as points and observable at the postcode level. Using UPC as a common field allows the concatenation of variables from disparate data sources that can potentially support sophisticated spatial analysis. However, visualising UPC in urban areas has at least three limitations. First, at small scales UPC occurrences can be very dense making their visualisation as points difficult. On the other hand, patterns in the associated attribute values are often hardly recognisable at large scales. Secondly, UPC can be used as a common field to allow the concatenation of highly multivariate data sets with an associated postcode. Finally, socio-economic variables assigned to UPC (such as the ones used here) can be non-Normal in their distributions as a result of a large presence of zero values and high variances which constrain their analysis using traditional statistics. This paper discusses a Point Visualisation Tool (PVT), a proof-of-concept system developed to visually explore point data. Various well-known visualisation techniques were implemented to enable their interactive and dynamic interrogation. PVT provides multiple representations of point data to facilitate the understanding of the relations between attributes or variables as well as their spatial characteristics. Brushing between alternative views is used to link several representations of a single attribute, as well as to simultaneously explore more than one variable. PVT’s functionality shows how the use of visual techniques embedded in an interactive environment enable the exploration of large amounts of multivariate point data

Non-visual overviews of complex data sets

This paper describes the design and preliminary testing of an interface to obtain overview information from complex numerical data tables non-visually, which is something that cannot be done with currently available accessibility tools for the blind and visually impaired users. A sonification technique that hides detail in the data and highlights its main features without doing any computations to the data, is combined with a graphics tablet for focus+context interactive navigation, in an interface called TableVis. Results from its evaluation suggest that this technique can deliver better scores than speech in time to answer overview questions, correctness of the answers and subjective workload

Picture this: researching child workers

Visual methods such as photography are under-used in the active process of sociological research. As rare as visual methods are, it is even rarer for the resultant images to be made by rather than of research participants. Primarily, the paper explores the challenges and contradictions of using photography within a multi-method approach. We consider processes for analysing visual data, different ways of utilising visual methods in sociological research, and the use of primary and secondary data, or, simple illustration versus active visual exploration of the social. The question of triangulation of visual data against text and testimony versus a stand-alone approach is explored in depth

A visual conflict hypothesis for global-local visual deficits in Williams Syndrome: simulations and data

Individuals with Williams Syndrome demonstrate impairments in visuospatial cognition. This has been ascribed to a local processing bias. More specifically, it has been proposed that the deficit arises from a problem in disengaging attention from local features. We present preliminary data from an integrated empirical and computational exploration of this phenomenon. Using a connectionist model, we first clarify and formalize the proposal that visuospatial deficits arise from an inability to locally disengage. We then introduce two empirical studies using Navon-style stimuli. The first explored sensitivity to local vs. global features in a perception task, evaluating the effect of a manipulation that raised the salience of global organization. Thirteen children with WS exhibited the same sensitivity to this manipulation as CA-matched controls, suggesting no local bias in perception. The second study focused on image reproduction and demonstrated that in contrast to controls, the children with WS were distracted in their drawings by having the target in front of them rather than drawing from memory. We discuss the results in terms of an inability to disengage during the planning stage of reproduction due to over-focusing on local elements of the current visual stimulus