Smart Camera Based Monitoring System and Its Application to Assisted Living
ABSTRACT Western societies are aging rapidly. An automated 24/7 surveillance to ensure safety of the elderly while respecting privacy becomes a major challenge. At the same time this is representative of novel and emerging video surveillance applications discovered lately besides the classic surveillance protection applications in airports, government buildings, and industrial plants. Three problems of current surveillance systems are identified. A distributed and automated smart camera based approach is proposed that addresses these problems. The proposed system's goal set is to analyze the real world and reflect all relevant-and only relevant-information live in an integrated virtual counterpart for visualization. It covers georeferenced person tracking and activity recognition (falling person detection). A prototype system installed in a home for assisted living has been running 24/7 for several months now and shows quite promising performance.
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ABSTRACT: This work proposes a method for automatic face obscuration capable of protecting people’s identity. Since face detection heavily benefits from the possibility to exploit tracking, multi-camera people tracking has been integrated with a face detector based on colour clustering and Hough transform. Moreover, the multiple viewpoints provided by multiple cameras are exploited in order to always obtain a good-quality image of the face. The identity of people in different views is kept consistent by means of a geometrical, uncalibrated approach based on homographies. Experimental results show the accuracy of the proposed approach.Pattern Recognition Letters. 01/2006;
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ABSTRACT: Efficient and comfortable acquisition of large 3D scenes is an important topic for many current and future applications in the field of robotics, factory and office visualization, 3DTV and cultural heritage.In this paper we present both an omnidirectional stereo vision approach for 3D modeling based on graph cut techniques and also a new mobile D model acquisition platform where it is employed. The platform comprises a panoramic camera and a 2D laser range scanner for self localization by scan matching. 3D models are acquired just by moving the platform around and recording images in regular intervals. Additionally, we concurrently build 3D models using two supplementary laser range scanners. This enables the investigation of the stereo algorithm’s quality by comparing it with the laser scanner based D model as ground truth. This offers a more objective point of view on the achieved D model quality.Image Vision Comput. 01/2009; 27:141-152.
Conference Proceeding: Analysis and Detection of Shadows in Video Streams: A Comparative Evaluation.[show abstract] [hide abstract]
ABSTRACT: Robustness to changes in illumination conditions as well as viewing perspectives is an important requirement for many computer vision applications. One of the key factors in enhancing the robustness of dynamic scene analysis is that of accurate and reliable means for shadow detection. Shadow detection is critical for correct object detection in image sequences. Many algorithms have been proposed in the literature that deal with shadows. However, a comparative evaluation of the existing approaches is still lacking. In this paper, the full range of problems underlying the shadow detection is identified and discussed. We classify the proposed solutions to this problem using a taxonomy of four main classes, deterministic model and non-model based, and statistical parametric and nonparametric. Novel quantitative (detection and discrimination accuracy) and qualitative metrics (scene and object independence, flexibility to shadow situations and robustness to noise) are proposed to evaluate these classes of algorithms on a benchmark suite of indoor and outdoor video sequences.2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), with CD-ROM, 8-14 December 2001, Kauai, HI, USA; 01/2001