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The quality of a shape-from-silhouettes 3D reconstruction technique strongly depends on the completeness of the silhouettes from each of the cameras. Static occlusion, due to e.g. furniture, makes reconstruction difficult, as we assume no prior knowledge concerning shape and size of occluding objects in the scene. In this paper we present a self-learning algorithm that is able to build an occlusion...
The trend towards mass customization has led to a significant increase of the complexity of manufacturing systems. Models to evaluate the complexity have been developed, but the complexity analysis of work stations is still done manually. This paper describes an automated analysis tool that makes us of multi-camera video images to support the complexity analysis of assembly line work stations.
People localization and occupancy mapping are common and important tasks for multi-camera systems. In this paper, we present a novel approach to overcome the hurdle of manual extrinsic calibration of the multi-camera system. Our approach is completely parameter unaware, meaning that the user does not need to know the focal length, position or viewing angle in advance, nor will these values be calibrated...
Foreground detection is an essential preprocessing step for many image processing applications such as object tracking, human action recognition, pose estimation and occupancy mapping. Many existing techniques only perform well under steady illumination. Some approaches have been introduced to detect foreground under varying or sudden changes in illumination but the problem remains challenging. In...
One of the most popular methods to extract information from an image sequence is template matching. The principle of template matching is tracking a certain feature or target over time based on the comparison of the content of each frame with a simple template. In this article, we propose an correlation coefficient based template matching which is invariant to linear intensity distortions to do correction...
Generally, image processing algorithms are suitable for parallel execution. However, this has not yet been exploited in a feasible design. Instead of the common practice, where the pixels on the sensor and the processor arrays are mapped onto each other, we propose the idea to split the image into multiple blocks of pixels (of the same size) and map each of these blocks onto one processing element...
In ambient intelligence object recognition is an important step towards behaviour analysis and the understanding interactions between people and the environment. Existing methods focus on a detailed analysis of image content using colour, shape, texture and motion analysis (direct recognition). In this paper we present a method for recognizing furniture, i.e. chairs, tables and the walking area in...
This paper proposes a novel method for detecting hand-raising gestures in meeting room and classroom environments. The proposed method first detects faces in each frame of the video sequence in order to define the region of interest (ROI). Then the system locates arms in the region of interest by analyzing the geometric structure of edges on the arm instead of directly detecting the hand. The location...
This demo paper introduces a flexible 3D visualization framework that can visualize an abstract representation of real-world events such as human movement and human interaction in an immersive way by rendering animated avatars. In the presented demo, events are detected and sent to the visualization by a multi-camera room occupancy monitoring system that uses video analysis to track people in a room...
In this demo we present a people tracker in indoor environments. The tracker executes in a network of smart cameras with overlapping views. Special attention is given to real-time processing by distribution of tasks between the cameras and the fusion server. Each camera performs tasks of processing the images and tracking of people in the image plane. Instead of camera images, only metadata (a bounding...
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