SceneFlowFields: Dense Interpolation of Sparse Scene Flow Correspondences

While most scene flow methods use either variational optimization or a strong rigid motion assumption, we show for the first time that scene flow can also be estimated by dense interpolation of sparse matches. To this end, we find sparse matches across two stereo image pairs that are detected without any prior regularization and perform dense interpolation preserving geometric and motion boundaries by using edge information. A few iterations of variational energy minimization are performed to refine our results, which are thoroughly evaluated on the KITTI benchmark and additionally compared to state-of-the-art on MPI Sintel. For application in an automotive context, we further show that an optional ego-motion model helps to boost performance and blends smoothly into our approach to produce a segmentation of the scene into static and dynamic parts.Comment: IEEE Winter Conference on Applications of Computer Vision (WACV), 201

Learning Rank Reduced Interpolation with Principal Component Analysis

In computer vision most iterative optimization algorithms, both sparse and dense, rely on a coarse and reliable dense initialization to bootstrap their optimization procedure. For example, dense optical flow algorithms profit massively in speed and robustness if they are initialized well in the basin of convergence of the used loss function. The same holds true for methods as sparse feature tracking when initial flow or depth information for new features at arbitrary positions is needed. This makes it extremely important to have techniques at hand that allow to obtain from only very few available measurements a dense but still approximative sketch of a desired 2D structure (e.g. depth maps, optical flow, disparity maps, etc.). The 2D map is regarded as sample from a 2D random process. The method presented here exploits the complete information given by the principal component analysis (PCA) of that process, the principal basis and its prior distribution. The method is able to determine a dense reconstruction from sparse measurement. When facing situations with only very sparse measurements, typically the number of principal components is further reduced which results in a loss of expressiveness of the basis. We overcome this problem and inject prior knowledge in a maximum a posterior (MAP) approach. We test our approach on the KITTI and the virtual KITTI datasets and focus on the interpolation of depth maps for driving scenes. The evaluation of the results show good agreement to the ground truth and are clearly better than results of interpolation by the nearest neighbor method which disregards statistical information.Comment: Accepted at Intelligent Vehicles Symposium (IV), Los Angeles, USA, June 201

Cognitive Principles of Schematisation for Wayfinding Assistance

People often need assistance to successfully perform wayfinding tasks in unfamiliar environments. Nowadays, a huge variety of wayfinding assistance systems exists. All these systems intend to present the needed information for a certain wayfinding situation in an adequate presentation. Some wayfinding assistance systems utilize findings for the field of cognitive sciences to develop and design cognitive ergonomic approaches. These approaches aim to be systems with which the users can effortless interact with and which present needed information in a way the user can acquire the information naturally. Therefore it is necessary to determinate the information needs of the user in a certain wayfinding task and to investigate how this information is processed and conceptualised by the wayfinder to be able to present it adequately. Cognitive motivated schematic maps are an example which employ this knowledge and emphasise relevant information and present it in an easily readable way. In my thesis I present a transfer approach to reuse the knowledge of well-grounded knowledge of schematisation techniques from one externalisation such as maps to another externalization such as virtual environments. A analysis of the informational need of the specific wayfinding task route following is done one the hand of a functional decomposition as well as a deep analysis of representation-theoretic consideration of the external representations maps and virtual environments. Concluding from these results, guidelines for transferring schematisation principles between different representation types are proposed. Specifically, this thesis chose the exemplary transfer of the schematisation technique wayfinding choremes from a map presentation into a virtual environment to present the theoretic requirements for a successful transfer. Wayfinding choremes are abstract mental concepts of turning action which are accessible as graphical externalisation integrated into route maps. These wayfinding choremes maps emphasis the turning action along the route by displaying the angular information as prototypes of 45° or 90°. This schematisation technique enhances wayfinding performance by supporting the matching processes between the map representation and the internal mental representation of the user. I embed the concept of wayfinding choremes into a virtual environment and present a study to test if the transferred schematisation technique also enhance the wayfinding performance. The empirical investigations present a successful transfer of the concept of the wayfinding choremes. Depending on the complexity of the route the embedded schematization enhance the wayfinding performance of participants who try to follow a route from memory. Participants who trained and recall the route in a schematised virtual environment make fewer errors than the participants of the unmodified virtual world. This thesis sets an example of the close research circle of cognitive behavioural studies to representation-theoretical considerations to applications of wayfinding assistance and their evaluations back to new conclusions in cognitive science. It contributes an interdisciplinary comprehensive inspection of the interplay of environmental factors and mental processes on the example of angular information and mental distortion of this information

Cognitive Principles of Schematisation for Wayfinding Assistance

People often need assistance to successfully perform wayfinding tasks in unfamiliar environments. Nowadays, a huge variety of wayfinding assistance systems exists. All these systems intend to present the needed information for a certain wayfinding situation in an adequate presentation. Some wayfinding assistance systems utilize findings for the field of cognitive sciences to develop and design cognitive ergonomic approaches. These approaches aim to be systems with which the users can effortless interact with and which present needed information in a way the user can acquire the information naturally. Therefore it is necessary to determinate the information needs of the user in a certain wayfinding task and to investigate how this information is processed and conceptualised by the wayfinder to be able to present it adequately. Cognitive motivated schematic maps are an example which employ this knowledge and emphasise relevant information and present it in an easily readable way. In my thesis I present a transfer approach to reuse the knowledge of well-grounded knowledge of schematisation techniques from one externalisation such as maps to another externalization such as virtual environments. A analysis of the informational need of the specific wayfinding task route following is done one the hand of a functional decomposition as well as a deep analysis of representation-theoretic consideration of the external representations maps and virtual environments. Concluding from these results, guidelines for transferring schematisation principles between different representation types are proposed. Specifically, this thesis chose the exemplary transfer of the schematisation technique wayfinding choremes from a map presentation into a virtual environment to present the theoretic requirements for a successful transfer. Wayfinding choremes are abstract mental concepts of turning action which are accessible as graphical externalisation integrated into route maps. These wayfinding choremes maps emphasis the turning action along the route by displaying the angular information as prototypes of 45° or 90°. This schematisation technique enhances wayfinding performance by supporting the matching processes between the map representation and the internal mental representation of the user. I embed the concept of wayfinding choremes into a virtual environment and present a study to test if the transferred schematisation technique also enhance the wayfinding performance. The empirical investigations present a successful transfer of the concept of the wayfinding choremes. Depending on the complexity of the route the embedded schematization enhance the wayfinding performance of participants who try to follow a route from memory. Participants who trained and recall the route in a schematised virtual environment make fewer errors than the participants of the unmodified virtual world. This thesis sets an example of the close research circle of cognitive behavioural studies to representation-theoretical considerations to applications of wayfinding assistance and their evaluations back to new conclusions in cognitive science. It contributes an interdisciplinary comprehensive inspection of the interplay of environmental factors and mental processes on the example of angular information and mental distortion of this information

Mobile Augmented Reality: Applications and Spe-cific Technical Issues

DOI: 10.1007/978-3-319-04702-7 Print ISBN: 978-3-319-04701-0 Online ISBN: 978-3-319-04702-7Although human's sedentary nature over time, his wish to travel the world remains as strong as ever. This paper discusses how imagery and Augmented Reality (AR) techniques can be of great help not only when discovering a new urban environment but also when observ-ing the evolution of the natural environment. The study is applied on Smartphone which is currently our most familiar device. Smart phone is utilized in our daily lives because it is low weight, ease of communications, and other valuable applications. In this chapter, we discuss technical issues of augmented reality especially with building recognition. Our building recog-nition method is based on an efficient hybrid approach, which combines the potentials of Speeded Up Robust Features (SURF) features points and lines. Our method relies on Approxi-mate Nearest Neighbors Search approach (ANNS). Although ANNS approaches are high speed, they are less accurate than linear algorithms. To assure an optimal trade-off between speed and accuracy, the proposed method performs a filtering step on the top of the ANNS. Finally, our method calls Hausdorff measure [15] with line models