2015 IEEE 18th International Conference on Intelligent Transportation Systems, 2015
This work contributes to vision processing for Advanced Driver Assist Systems (ADAS) and intellig... more This work contributes to vision processing for Advanced Driver Assist Systems (ADAS) and intelligent vehicle applications. We propose a color-only stixel segmentation framework to segment traffic scenes into free, drivable space and obstacles, which has a reduced latency to improve the real-time processing capabilities. Our system learns color appearance models for free-space and obstacle classes in an online and self-supervised fashion. To this end, it applies a disparitybased segmentation, which can run in the background of the critical system path, either with a time delay of several frames or at a frame rate that is only a third of that of the color-based algorithm. In parallel, the most recent video frame is analyzed solely with these learned color appearance models, without an actual disparity estimate and the corresponding latency. This translates into a reduced response time from data acquisition to data analysis, which is a critical property for high-speed ADAS. Our evaluation on two publicly available datasets, one of which we introduce as part of this work, shows that the color-only analysis can achieve similar or even better results in difficult imaging conditions, compared to the disparity-only method. Our system improves the quality of the free-space analysis, while simultaneously lowering the latency and the computational load.
Television system for transmitting digitized television pictures from a transmitter to a receiver where different transform coding techniques are selected on the determination of motion
2006 IEEE International Conference on Multimedia and Expo, 2006
The low bit rate of existing video encoders relies heavily on the accuracy of estimating actual m... more The low bit rate of existing video encoders relies heavily on the accuracy of estimating actual motion in the input video sequence. In this paper, we propose a Video Stabilization and Encoding (ViSE) system to achieve a higher coding efficiency through a preceding motion processing stage (to the compression), of which the stabilization part should compensate for vibrating camera motion. The improved motion prediction is obtained by differentiating between the temporal coherent motion and a more noisy motion component which is orthogonal to the coherent one. The system compensates the latter undesirable motion, so that it is eliminated prior to video encoding. To reduce the computational complexity of integrating a digital stabilization algorithm with video encoding, we propose a system that reuses the already evaluated motion vector from the stabilization stage in the compression. As compared to H.264, our system shows a 14% reduction in bit rate yet obtaining an increase of about 0.5 dB in SNR.
This paper presents an advanced video navigation concept based on a Picture in Picture (PiP) allo... more This paper presents an advanced video navigation concept based on a Picture in Picture (PiP) allowing combined rendering of fragments of normal-play video and fast search video simultaneously. Loss of audio during conventional fast search trick-play is eliminated, by adding the sound of the normal play fragment. The normal-play fragments provide detailed information, whereas the fast-search signal presents a course overview. The audio associated to the normal-play fragments enhances the navigation process, allowing the viewer to concentrate on either the normal play or the fast search window. Efficient signal processing in the MPEG-2 domain permits re-use of the standard MPEG-2 decoding path for decoding the normal play audiovisual fragments. Applying a scalable MPEG-2 decoder for decoding the fast search signal enables a low-cost implementation for Personal Video Recording (PVR).
2006 IEEE International Conference on Multimedia and Expo, 2006
This paper presents a layered framework for 3D-TV applications, combining multiview and depth-ima... more This paper presents a layered framework for 3D-TV applications, combining multiview and depth-image based approaches in a scalable fashion. To solve the problem of missing data due to disocclusions, we add specific layers for coded occlusion data and the edge-mask information for high-quality 3D rendering of key objects in the scene. We show how the same framework can be extended towards FTV applications by jointly addressing simulcast and multicast transmission. By adopting a distributed delivery architecture, new interesting properties can be realized such as shared processing for the creation and streaming of virtual viewpoints.
Background Estimation and Adaptation Model with Light-Change Removal for Heavily Down-Sampled Video Surveillance Signals
2006 International Conference on Image Processing, 2006
BACKGROUND ESTIMATION AND ADAPTATION MODEL WITH LIGHT-CHANGE REMOVAL FOR HEAVILY DOWN-SAMPLED VID... more BACKGROUND ESTIMATION AND ADAPTATION MODEL WITH LIGHT-CHANGE REMOVAL FOR HEAVILY DOWN-SAMPLED VIDEO SURVEILLANCE SIGNALS Sascha Cvetkovic *, Peter Bakker , Johan Schirris * Bosch Security Systems 5616LW-2 Eindhoven, The Netherlands ...
A toolkit for design and performance analysis of real-time component-based software systems
Abstract—Software tools supporting the design and analysis of complex software-intensive systems ... more Abstract—Software tools supporting the design and analysis of complex software-intensive systems are highly desirable, since they enable earlier decision making about system realization. This paper presents a tooling environment that supports the design and performance analysis ...
In this paper, we propose a cascaded facial feature-extraction framework employing a set of model... more In this paper, we propose a cascaded facial feature-extraction framework employing a set of model-based algorithms. In this framework, the algorithms are arranged with increasing model flexibility and extraction accuracy, such that the cascaded algorithm can have an optimal performance in both robustness and extraction accuracy. Especially, we propose a set of guidelines to analyze and jointly optimize the performance relation between the constituting algorithms, such that the constructed cascade gives the best overall performance. Afterwards, we present an implementation of the cascaded framework employing three algorithms, namely, sparse-graph search, component-based texture fitting and component-based direct fitting. Special attention is paid on the search and optimization of the model parameters of each algorithm, such that the overall extraction performance is greatly improved with respect to both reliability and accuracy. r
Scalable implementations of multimedia applications offer increased flexibility in mapping those ... more Scalable implementations of multimedia applications offer increased flexibility in mapping those applications onto the executing platform used in a consumer product. In this paper, we describe a hierarchical Quality-of-Service (QoS) model for managing multimedia applications running on a multiprocessor Systems-on-Chip (SoC). First, we present the possible scalability of an MPEG-4 arbitraryshaped video decoder with respect to computational and communicational resources. Second, we provide a novel model for QoS management based on the principles of predictable mapping and run-time information on the resource utilization. We demonstrate the QoS framework by mapping of an MPEG-4 arbitrary-shaped decoder on a NoC, employing eight ARM cores with specific monitoring features in the network (e.g. AEthereal NoC). The scalable implementation results in lowering the computational requirements by 26% and communication by 43%. Experiments revealed that the combination results in more than 85% decoded frames of higher quality than in a QoS approach based on the predictable mapping 1 only.
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Papers by Peter de With