Jens Maiero

Robust indoor localization using optimal fusion filter for sensors and map layout information

A person has to deal with large and unknown scenarios, for example a client searching for a expositor in a trade fair or a passenger looking for a gate in an airport. Due to the fact that position awareness represents a great advantage for people, a navigation system implemented for a commercial smartphone can help the user to save time and money. In this work a navigation example application able to localize and provide directions to a desired destination in an indoor environment is presented and evaluated. The position of the user is calculated with information from the smartphone builtin sensors, WiFi adapter and floor-plan layout of the indoor environment. A commercial smartphone is used as the platform to implement the example application, due to its hardware features, computational power and the graphic user interface available for the users. Evaluations verified that room accuracy is achieved for robust localization by using the proposed technologies and algorithms. The used optimal sensor fusion filter for different sources of information and the easy to deploy infrastructure in a new environment show promise for mobile indoor navigation systems.

Pedestrian indoor positioning using smartphone multi-sensing, radio beacons, user positions probability map and IndoorOSM floor plan representation

Position awareness in unknown and large indoor spaces represents a great advantage for people, everyday pedestrians have to search for specific places, products and services. In this work a positioning solution able to localize the user based on data measured with a mobile device is described and evaluated. The position estimate uses data from smartphone built-in sensors, WiFi (Wireless Fidelity) adapter and map information of the indoor environment (e.g. walls and obstacles). A probability map derived from statistical information of the users tracked location over a period of time in the test scenario is generated and embedded in a map graph, in order to correct and combine the position estimates under a Bayesian representation. PDR (Pedestrian Dead Reckoning), beacon-based Weighted Centroid position estimates, map information obtained from building OpenStreetMap XML representation and probability map users path density are combined using a Particle Filter and implemented in a smartphone application. Based on evaluations, this work verifies that the use of smartphone hardware components, map data and its semantic information represented in the form of a OpenStreetMap structure provide 2.48 meters average error after 1,700 travelled meters and a scalable indoor positioning solution. The Particle Filter algorithm used to combine various sources of information, its radio WiFi-based observation, probability particle weighting process and the mapping approach allowing the inclusion of new indoor environments knowledge show a promising approach for an extensible indoor navigation system.

Guided High-Quality Rendering

We present a system which allows for guiding the image quality in global illumination (GI) methods by user-specified regions of interest (ROIs). This is done with either a tracked interaction device or a mouse-based method, making it possible to create a visualization with varying convergence rates throughout one image towards a GI solution. To achieve this, we introduce a scheduling approach based on Sparse Matrix Compression (SMC) for efficient generation and distribution of rendering tasks on the GPU that allows for altering the sampling density over the image plane. Moreover, we present a prototypical approach for filtering the newly, possibly sparse samples to a final image. Finally, we show how large-scale display systems can benefit from rendering with ROIs.

ForceTab: Visuo-haptic interaction with a force-sensitive actuated tablet

Enhancing touch screen interfaces through non-visual cues has been shown to improve performance. In this paper we report on a novel system that explores the usage of a forcesensitive motion-platform enhanced tablet interface to improve multi-modal interaction based on visuo-haptic instead of tactile feedback. Extending mobile touch screen with force-sensitive haptic feedback has potential to enhance performance interacting with GUIs and to improve perception of understanding relations. A user study was performed to determine the perceived recognition of different 3D shapes and the perception of different heights. Furthermore, two application scenarios are proposed to explore our proposed visuo-haptic system. The studies show the positive stance towards the feedback, as well as the found limitations related to perception of feedback.

PICOZOOM: A context sensitive multimodal zooming interface

This paper introduces a novel zooming interface deploying a pico projector that, instead of a second visual display, leverages audioscapes for contextual information. The technique enhances current flashlight metaphor approaches, supporting flexible usage within the domain of spatial augmented reality to focus on object or environment-related details. Within a user study we focused on quantifying the projection limitations related to depiction of details through the pico projector and validated the interaction approach. The quantified results of the study correlate pixel density, detail and proximity, which can greatly aid to design more effective, legible zooming interfaces for pico projectors - the study can form an example testbed that can be applied well for testing aberrations with other projectors. Furthermore, users rated the zooming technique using audioscapes well, showing the validity of the approach. The studies form the foundation for extending our work by detailing out the audio-visual approach and looking more closely in the role of real-world features on interpreting projected content.

Focus-Plus-Context Techniques for Picoprojection-Based Interaction

In this paper, we report on novel zooming interface methods that deploy a small handheld projector. Using mobile projections to visualize object/environment-related information on real objects introduces new aspects for zooming interfaces. Different approaches are investigated that focus on maintaining a level of context while exploring detailed information. Doing so, we propose methods that provide alternative contextual cues within a single projector and deploy the potential of zoom lenses to support a multilevel zooming approach. Furthermore, we look into the correlation between pixel density, distance to the target, and projection size. Alongside these techniques, we report on multiple user studies, in which we quantified the projection limitations and validated various interactive visualization approaches. Thereby, we focused on solving issues related to pixel density, brightness, and contrast that affect the design of more effective legible zooming interfaces for handheld projectors.

Lazy details for large high-resolution displays

Rendering techniques for design evaluation and review or for visualizing large volume data often use computationally expensive ray-based methods. Due to the number of pixels and the amount of data, these methods often do not achieve interactive frame rates. A view direction based rendering technique renders the users central field of view in high quality whereas the surrounding is rendered with a level of detail approach depending on the distance to the users central field of view thus giving the opportunity to increase rendering efficiency. We propose a prototype implementation and evaluation of a focus-based rendering technique based on a hybrid ray tracing/sparse voxel octree rendering approach.

FPGA-based image combiner for parallel rendering

Rendering of virtual scenes is an application that still demands higher computing power for more complex and more realistic scenes. In addition to existing parallel processing inside a graphics processing unit, this paper investigates a further level of parallelization. A combiner based on an FPGA (field programmable gate array) allows to merge the graphics output of several independent computers. The image combiner supports different load distribution techniques, namely sort-first and sort-last rendering. A system prototype based on a commercial evaluation system proved the viability of the approach. A compact and cost-efficient dedicated implementation has been designed and is used as a platform to investigate different approaches for parallel rendering.

A Method for Fast Initialization of Markerless Object Tracking

In Mixed Reality (MR) Environments, the user’s view is augmented with virtual, artificial objects. To visualize virtual objects, the position and orientation of the user’s view or the camera is needed. Tracking of the user’s viewpoint is an essential area in MR applications, especially for interaction and navigation. In present systems, the initialization is often complex. For this reason, we introduce a new method for fast initialization of markerless object tracking. This method is based on Speed Up Robust Features and paradoxically on a traditional markerbased library. Most markerless tracking algorithms can be divided into two parts: an offline and an online stage. The focus of this paper is optimization of the offline stage, which is often time-consuming.