Shadow Removal for Greyscale Video Sequences

Kryjak, Tomasz

doi:10.2478/v10248-012-0037-8

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…By using masks defined during the configuration phase the detection of emergency situations in the scenarios "violation of protected zones" and "vandalism: graffiti" is immediate. The detection algorithm of zones' violation works correctly, but it is planned its supplement with one of the methods of shadows removal [22].…”

Section: Resultsmentioning

confidence: 99%

Realization of Scenarios for Video Surveillance

Chmiel

Kwiecień

Mikrut

2012

Image Processing & Communications

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The design of a methodology for the effective scene understanding systems is one of the main goals of the researchers in the analysis of video surveillance. The objects in the scene have to be identified. Hence, it is necessary to detect the parts belonging to the background. In the article we introduce the base algorithms, which enable us to realization of scenarios. We briefly describe base algorithms (object detection, object localization, recognition of humans, movement detection and configuration of scene) used in three selected scenarios: violation of protected zones, abandoned objects and vandalism (graffiti). These scenarios were tested on several films, obtained from Internet and made by participants of project SIMPOZ. The results of our experiments are presented. The basic algorithms for detecting and locating objects are very quickly, but movement detection ("optical flow") and recognition of humans algorithms work longer.

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Section: Resultsmentioning

confidence: 99%

Realization of Scenarios for Video Surveillance

Chmiel

Kwiecień

Mikrut

2012

Image Processing & Communications

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“…(a) The selected frame from the PETS 2006 dataset [1], (b) a foreground object mask (from the back-ground estimation module), (c) a foreground mask after postprocessing, (d) Connected component analysis results to the system, or may be a noise pixels and irrelevant artifacts. Hence, results from the detection module are transferred to the analysis level.The detection module can be easily extended, for example by utilizing the shadow removal algorithm[8].…”

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confidence: 99%

Object detection and tracking for low-cost video surveillance system

Przybyło

2013

Image Processing & Communications

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Automated and intelligent video surveillance systems play important role in the modern world. Since the amount of various video streams that must be analyzed grows, such artificial intelligence systems can assist humans in performing tiresome tasks. As a result, the effectiveness of response to a dangerous situations is increasing (detect unexpected movement or unusual behavior that may pose a threat to people, property and infrastructure). Video surveillance systems have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide a sufficient response time. The work presented here focuses on the selected challenges of scene analysis in video surveillance systems (object detection/tracking, effectiveness of the whole system). The aim of the research is to design a low-budget surveillance system, that can be used for example in a home security monitoring. Such solution can be use not only to surveillance but also to monitor elderly person at home or provide new ways of interacting in human-computer interaction systems.

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Shadow Removal for Greyscale Video Sequences

Cited by 2 publications

References 15 publications

Realization of Scenarios for Video Surveillance

Realization of Scenarios for Video Surveillance

Object detection and tracking for low-cost video surveillance system

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