Julien A. Vijverberg

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This paper presents a background segmentation technique, which is able to process acceptable segmentation masks under fast global illumination changes. The histogram of the frame-based background difference is modeled with multiple kernels. The model that represents the histogram at best, is used to determine the shift in luminance due to global(More)
This paper presents the design of a robust and real-time traffic-violation detection system for cameras on intersections. We use background segmentation and a novel road-model to obtain the candidate traffic participants. A region-based tracking system, equipped with static occlusion-reasoning, tracks the positions of the objects in the scene. A(More)
This paper discusses the design of embedded multiprocessor architectures for pixel-level video-content analysis applications in video sequences. First, a number of object segmentation computing tasks are analyzed. In order to come to an efficient proposal for a content-analysis processing platform, we have taken five different representative applications(More)
With the growing number of video content analysis applications, efficient implementation has become increasingly important. Video-object tracking using image moments is an important subtask in video-content analysis content algorithms. In this paper, we will present a method of accelerating the computation of geometrical moments and the resulting moment(More)
This paper considers the problem of tracking a variable number of objects through a surveillance site monitored by multiple cameras with slightly overlapping field-of-views. To this end, we propose to cluster tracklets generated by a commercially available single-camera video-analysis algorithm which is solely based on the position of objects. A first(More)
This paper describes the application of a Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter for tracking objects in surveillance video. Clark et al. have proposed a point-based GM-PHD filter designed for track label consistency. However, this cannot be used for track consistency when using rectangles covering an object. The proposed solution(More)
This paper considers tracking of objects for video-based intrusion detection systems. Current tracking algorithms can be used for surveillance, but in that use-case, these algorithms execute with too high latency and are not suitable for real-time applications. In this paper, we propose novel techniques for tracking algorithms based on tracklets in order to(More)
This paper presents ongoing work on the design of a two-dimensional (2D) systolic array for image processing. This component is designed to operate on a multi-processor system-on-chip. In contrast with other 2D systolicarray architectures and many other hardware accelerators, we investigate the applicability of executing multiple tasks in a time-interleaved(More)
This paper proposes two novel motion-vector based techniques for target detection and target tracking in surveillance videos. The algorithms are designed to operate on a resource-constrained device, such as a surveillance camera, and to reuse the motion vectors generated by the video encoder. The first novel algorithm for target detection uses motion(More)
This paper describes a novel model for training an event detection system based on object tracking. We propose to model the training as a multiple instance learning problem, which allows us to train the classifier from annotated events despite temporal ambiguities. We apply this technique to realize a Perimeter Intrusion Detection (PID) algorithm and employ(More)
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