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Chapter
Infizierte Demokratien? Pandemiepolitik und Demokratiequalität in Argentinien, Mexiko und Uruguay
Die Covid-19-Pandemie stellt eine besondere Herausforderung für die Demokratien in Lateinamerika dar. Uwe Franke, Veit Straßner und Christoph Wagner behandeln den Zusammenhang zwischen Pandemiepolitik und Demokra...
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Article
Open AccessSlanted Stixels: A Way to Represent Steep Streets
This work presents and evaluates a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive geometric assumptio...
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Chapter and Conference Paper
Workshop on Interactive and Adaptive Learning in an Open World
Next generation machine learning requires step** away from classical batch learning towards interactive and adaptive learning. This is essential to cope with demanding machine learning applications we have a...
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Chapter and Conference Paper
Multimodal Neural Networks: RGB-D for Semantic Segmentation and Object Detection
This paper presents a novel multi-modal CNN architecture that exploits complementary input cues in addition to sole color information. The joint model implements a mid-level fusion that allows the network to e...
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Article
Context-based multi-target tracking with occlusion handling
Occlusion has long been a core challenge for multi-target tracking tasks. In this paper we present context-based tracking strategies and demonstrate those for two very different types of targets, namely vehicl...
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Chapter and Conference Paper
Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling
Recent approaches for instance-aware semantic labeling have augmented convolutional neural networks (CNNs) with complex multi-task architectures or computationally expensive graphical models. We present a meth...
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Chapter and Conference Paper
Semantically Guided Depth Upsampling
We present a novel method for accurate and efficient upsampling of sparse depth data, guided by high-resolution imagery. Our approach goes beyond the use of intensity cues only and additionally exploits object...
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Reference Work Entry In depth
Stereovision for ADAS
Camera-based driver assistance went from pure research level activities in the early 1990s to standard equipment products in vehicles nowadays. This change is due to both technological advances and algorithmic...
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Living Reference Work Entry In depth
Stereovision for ADAS
Camera-based driver assistance went from pure research level activities in the early 1990s to standard equipment products in vehicles nowadays. This change is due to both technological advances and algorithmic...
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Chapter and Conference Paper
What Is in Front? Multiple-Object Detection and Tracking with Dynamic Occlusion Handling
This paper proposes a multiple-object detection and tracking method that explicitly handles dynamic occlusions. A context-based multiple-cue detector is proposed to detect occluded vehicles (occludees). First,...
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Chapter
Dense 3D Motion Field Estimation from a Moving Observer in Real Time
In this chapter an approach for estimating the three-dimensional motion fields of real-world scenes is proposed. This approach combines state-of-the-art dense optical flow estimation, including spatial regular...
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Chapter and Conference Paper
Object-Level Priors for Stixel Generation
This paper presents a stereo vision-based scene model for traffic scenarios. Our approach effectively couples bottom-up image segmentation with object-level knowledge in a sound probabilistic fashion. The rele...
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Chapter and Conference Paper
Stixmantics: A Medium-Level Model for Real-Time Semantic Scene Understanding
In this paper we present Stixmantics, a novel medium-level scene representation for real-time visual semantic scene understanding. Relevant scene structure, motion and object class information is encoded using so...
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Chapter and Conference Paper
Know Your Limits: Accuracy of Long Range Stereoscopic Object Measurements in Practice
Modern applications of stereo vision, such as advanced driver assistance systems and autonomous vehicles, require highest precision when determining the location and velocity of potential obstacles. Subpixel d...
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Chapter and Conference Paper
Efficient Multi-cue Scene Segmentation
This paper presents a novel multi-cue framework for scene segmentation, involving a combination of appearance (grayscale images) and depth cues (dense stereo vision). An efficient 3D environment model is utili...
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Chapter and Conference Paper
Highly Accurate Depth Estimation for Objects at Large Distances
Precise stereo-based depth estimation at large distances is challenging: objects become very small, often exhibit low contrast in the image, and can hardly be separated from the background based on disparity d...
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Chapter and Conference Paper
Pixels, Stixels, and Objects
Dense stereo vision has evolved into a powerful foundation for the next generation of intelligent vehicles. The high spatial and temporal resolution allows for robust obstacle detection in complex inner city s...
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Article
Stereoscopic Scene Flow Computation for 3D Motion Understanding
Building upon recent developments in optical flow and stereo matching estimation, we propose a variational framework for the estimation of stereoscopic scene flow, i.e., the motion of points in the three-dimen...
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Chapter and Conference Paper
Illumination-Robust Dense Optical Flow Using Census Signatures
Vision-based motion perception builds primarily on the concept of optical flow. Modern optical flow approaches suffer from several shortcomings, especially in real, non-ideal scenarios such as traffic scenes. ...
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Chapter
Unternehmensverantwortung verbessert die Wirtschaftlichkeit
Kaum ein Begriff hat in den letzten Jahren so viele Erklärungsansätze provoziert wie Corporate Social Responsibility, die gesellschaftliche Verantwortung von Unternehmen. Wie weit geht die Verantwortung eines ...
