Use of feedback strategies in the detection of events for video surveillance
ABSTRACT The authors present a feedback-based approach for event detection in video surveillance that improves the detection accuracy and dynamically adapts the computational effort depending on the complexity of the analysed data. A core feedback structure is proposed based on defining different levels of detail for the analysis performed and estimating the complexity of the data being analysed. Then, three feedback-based analysis strategies are defined (based on this core structure) and introduced in the processing stages of a typical video surveillance system. A rule-based system is designed to manage the interaction between these feedback-strategies. Experimental results show that the proposed approach slightly increases the detection reliability, whereas highly reduces the computational effort as compared to the initially developed surveillance system (without feedback strategies) across a variety of multiple video surveillance scenarios operating at real time.
Conference Paper: Tools and techniques for video performance evaluation[Show abstract] [Hide abstract]
ABSTRACT: We outline a reconfigurable video performance evaluation resource (ViPER), which provides an interface for ground truth generation, metrics for evaluation and tools for visualization of video analysis results. A key component is that the approach provides the basic infrastructure, and allows users to configure data generation and evaluation. Although ViPER can be used for any type of data, we focus on applications which require video contentPattern Recognition, 2000. Proceedings. 15th International Conference on; 02/2000
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ABSTRACT: We present an encoding framework which exploits semantics for video content delivery. The video content is organized based on the idea of main content message. In the work reported in this paper, the main content message is extracted from the video data through semantic video analysis, an application-dependent process that separates relevant information from non relevant information. We use here semantic analysis and the corresponding content annotation under a new perspective: the results of the analysis are exploited for object-based encoders, such as MPEG-4, as well as for frame-based encoders, such as MPEG-1. Moreover, the use of MPEG-7 content descriptors in conjunction with the video is used for improving content visualization for narrow channels and devices with limited capabilities. Finally, we analyze and evaluate the impact of semantic video analysis in video encoding and show that the use of semantic video analysis prior to encoding sensibly reduces the bandwidth requirements compared to traditional encoders not only for an object-based encoder but also for a frame-based encoder.IEEE Transactions on Circuits and Systems for Video Technology 11/2005; DOI:10.1109/TCSVT.2005.854240 · 2.26 Impact Factor
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ABSTRACT: In this paper, we present an optimization-based system that automates home video editing. This system automatically selects suitable or desirable highlight segments from a set of raw home videos and aligns them with a given piece of incidental music ...IEEE Transactions on Circuits and Systems for Video Technology 06/2004; 14(5-14):569 - 571. DOI:10.1109/TCSVT.2004.828719 · 2.26 Impact Factor