Reliable motion detection of small targets in video with low signal-to-clutter ratios

Nichols, Scott; Naylor, R. B.

doi:10.1109/ccst.1995.524949

“…Diana presented target detection algorithm based on pipeline filter [7]. There are also some algorithms using likelihood ratio [8], neural network algorithm, the three dimensional spatial filter and two-dimensional matched filter [9] etc. they extracted the real goal from candidate target.…”

Section: Introductionmentioning

confidence: 99%

An Improved Method for Moving Target Detection Based on Spatial-temporal Fusion Filtering

Li¹,

Wu²,

Zou³

2016

Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

0

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Infrared weak small target detection is one of the key technologies in the infrared early warning system, infrared imaging guidance system and wide-field view surveillance system etc. In the complex and low signal-to-noise ratio background environment, the target has only a few pixels. There is no shape and texture information to use. All of the above issues bring great difficulties to infrared dim-small target detection. In this paper, in order to deal with the shortcoming of large pixel tracking in moving target detection algorithm based on time domain filtering, apply the dim target detection based on Laplace operator to the subject of this paper, the false alarm points obviously to be less, and the target point is usually in the form of a single pixel, lay a good foundation for reducing the complexity of the algorithm.

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Sensor fusion for intelligent alarm analysis

Nelson

¹

,

Fitzgerald

²

1997

IEEE Aerosp. Electron. Syst. Mag.

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RECElV MAR 1 5 19%The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low falsehuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infixed, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of I revolution per second to detect and track motion and provide assessment in a continuous 360" field-of-regard. Sensor hsion techniques are used to correlate and integrate the track data &om these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator. IntroductionA typical central alarm station for a security environment is an integrated system of people, procedures, and equipment. An alarm communication and display system receives alarm signals fiom intrusion detection sensors and displays the information to a security operator for action. Although annunciator displays observed by the operator are easy to understand and maintain, they typically contain only a limited amount of information. Therefore, the operator must manually assess each alarm occurrence, which could be difficult, time consuming, and error-prone. The idea behind intelligent alarm analysis (IAA) is to preprocess data from the security sensors and present alarm information to the security operator in a manner that would provide concise and meaningful information and increase confidence in true alarm events while filtering out the necessity to assess nuisance and false alarms. One of the goals of the IAA Project at Sandia National Laboratories is to devise this preprocessing methodology using alarm processing and fusion techniques on available sensor data.Initial intelligent alarm analysis concepts were developed for the Advanced Exterior Sensor (AES), an intrusion detection and assessment system currently being developed at Sandia. The AES requires the fusion of data

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Sensor fusion for intelligent alarm analysis

Nelson

¹

,

Fitzgerald²

Proceedings of IEEE International Carnahan Conference on Security Technology

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RECElV MAR 1 5 19%The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low falsehuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infixed, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of I revolution per second to detect and track motion and provide assessment in a continuous 360" field-of-regard. Sensor hsion techniques are used to correlate and integrate the track data &om these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator. IntroductionA typical central alarm station for a security environment is an integrated system of people, procedures, and equipment. An alarm communication and display system receives alarm signals fiom intrusion detection sensors and displays the information to a security operator for action. Although annunciator displays observed by the operator are easy to understand and maintain, they typically contain only a limited amount of information. Therefore, the operator must manually assess each alarm occurrence, which could be difficult, time consuming, and error-prone. The idea behind intelligent alarm analysis (IAA) is to preprocess data from the security sensors and present alarm information to the security operator in a manner that would provide concise and meaningful information and increase confidence in true alarm events while filtering out the necessity to assess nuisance and false alarms. One of the goals of the IAA Project at Sandia National Laboratories is to devise this preprocessing methodology using alarm processing and fusion techniques on available sensor data.Initial intelligent alarm analysis concepts were developed for the Advanced Exterior Sensor (AES), an intrusion detection and assessment system currently being developed at Sandia. The AES requires the fusion of data

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Reliable motion detection of small targets in video with low signal-to-clutter ratios

Cited by 4 publications

References 6 publications

An Improved Method for Moving Target Detection Based on Spatial-temporal Fusion Filtering

An Improved Method for Moving Target Detection Based on Spatial-temporal Fusion Filtering

Sensor fusion for intelligent alarm analysis

Sensor fusion for intelligent alarm analysis

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