Research Projects (2010)
- Show Keywords
- 3D Computer Vision 3D reconstruction Aerial Vision Augmented Reality Augmented Video Best Paper Award Biometrics Caleydo Computer Graphics Computer Vision Convex Optimization Coordinate transformations detection face Fingerprint Georeferencing GPU GUI HOG Human Computer Interaction Image Labelling Industrial Applications Information Visualization integral imaging Interaction Interaction Design Machine Learning Medical computer vision Medical Visualization Mixed Reality Mobile computing Mobile phone Model Multi-Display Environments Multiple Perspectives Object detection Object recognition Object reconstruction Object Tracking On-Line Learning Robotics Segmentation Shape analysis shape from focus SLAM Software Projects Structure from Motion Surveillance SVM Symmetry Tracking Fusion Tracking, Action Recognition User Interfaces Variational Methods Virtual reality and augmented reality Visual Tracking Visualization
| Title | Abstract |
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Mobi-Trick
(details) |
The focus of the project is outdoor mobile computer vision with all of its challenges. Mobile systems need to be compact and energy efficient and are frequently changing locations. Therefore they must be autonomous and perform processing locally. A number of challenges arise from these requirements for which the project aims to provide solutions: Being compact, there is not much space for a large number of sensors such as laser scanners, radar antennas and the like. The work in this project will focus on stereo vision but with two different types of cameras. Often a second camera is already available and stereo information increases detection accuracies. Each time the system moves it needs to adapt to the changing situation. This requires adaptive calibration and online learning. Mobile systems often work from batteries. In addition, there is not much space to include intricate cooling systems. Thus, the system must be designed to be very energy efficient. New approaches for dynamic power management will be explored in the project. To put the work into context, several applications from the area of traffic surveillance/toll enforcement will be implemented and tested in an application oriented setting. Current traffic enforcement solutions are either very large and costly (section control, toll enforcement) or do not offer much in terms of image processing (radar speed control). The technological output of Mobi Trick makes it possible to design mobile solutions for traffic monitoring, vehicle identification and classification, intelligent incident detection and observation of driver behavior. Mobile devices are also more efficient in enforcement. Their transient nature makes them less predictable. Mobile systems can also react more flexibly to changing road situations such as construction sites. |
2010 | 2013 |
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HD-VIP: High Definition Video Processing
(details) |
The growth of information is nowadays enormous and at a level which had never been reached before. We currently produce almost more data in one year than was produced in the entire history of mankind so far. In particular the trend to a full digitization of audiovisual content is contributing to this explosion of available material. The exponential growth of online video, most notably YouTube among the many prominent video portals is just one example for that. Even if international studies are not arriving at exactly the same results, the figures are impressive: digital production in 2006 was approximately 160 Exabyte, and is predicted to rise to 990 Exabyte in 2010. Any video processing /editing software has to keep pace with these extraordinary data rates which requires special efforts from the hardware and the software. Fortunately we see also an extraordinary increase in processing power, especially when looking at recent developments of graphics cards (GPUs). These cards offer massive parallelism (ideally suited for video processing) at a rather modest price. All these facts make this hardware an ideal candidate for video processing. But in order to make full use of the hardware the algorithms have to be highly parallel. Typical tasks encountered in video processing (which will also be tackled by the proposed project are): Superresolution: With the advent of HDTVs in many homes there is an increasing need to produce also HDTV content. In order to make use of existing (low-resolution) material one can use so called superresolution algorithms. These methods generate from a sequence of low resolution frames a high resolution image by exploiting the high interframe redundancy. Denoising: There are many sources of noise in a video, either the material is historic or during production/compression etc. noise is added to the video. A basic task is to remove the noise but still preserve all fine scale details. Interactive video editing: For post production purposes one wants to mark objects in a video (of course the object should only be marked in a single frame and then segmented automatically in all subsequent frames) and either remove them (which requires inpainting methods to fill the holes with meaningful content), place them somewhere else in the video or replace them with different objects. Since these tasks are done interactively this requires interactive framerates. Fortunately all of these tasks can be addressed by so called variational methods. The basic idea is to formulate the task as a minimization problem of a suitable energy functional. Besides other desirable properties these methods can be implemented in a highly parallel fashion which makes them ideal candidates for implementation on modern GPUs. |
2010 | 2012 |
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Highly accurate range computation in driver assistence systems
(details) |
In this project we study variational methods for computing highly accurate range data in driver assistance systems. |
2010 | 2011 |
