Cooperative Tracking Using Multiple PTZ Thermal Imagers

Li, Zhenghao; Hu, Ziqi; Li, Honghu; Fu, Shiqing

doi:10.1007/s10765-012-1303-0

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…PSO-PF first finds the sample area by PSO algorithm and then distributes the particles based on two different base points in order to achieve diversity and convergence in feature matching. For more details, please refer to [7].…”

Section: Cooperative Trackingmentioning

confidence: 99%

“…This is because existing solutions are generally based on motion detection that needs static background, but the FOV (Field of View) usually changed continuously when using PTZ cameras or thermal imagers. Thus, obtaining the FOV offset accurately and getting the thermal imager pose simultaneously are the key points to realize intrusion detection and cooperative tracking using PTZ network thermal imagers [7].…”

Section: Introductionmentioning

confidence: 99%

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Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

Yang

Han

et al. 2015

International Journal of Distributed Sensor Networks

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Nowadays more and more network thermal imaging cameras are working over distributed networks, offering the capability of online remote intelligent video surveillance. In this paper, we propose an original intrusion detection and cooperative tracking approach applied for PTZ (Pan/Tilt/Zoom) network thermal imagers. It consists of three modules. The key module is the real-time FOV (Field of View) matching module, which is realized in a parallel way. The intrusion detection module first eliminates the offset between current frame and prior frame through FOV matching and then handles intrusion detection by motion detection in the preset surveillance zone. The cooperative tracking module shifts the priority of tracking by imager pose estimation, which is also based on FOV matching, avoiding transferring the local features from one imager to another. Experiments are conducted to demonstrate that the proposed approach is of high accuracy for intrusion detection and cooperative tracking and keeps the frame rate over 20 fps.

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Section: Cooperative Trackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

Yang

Han

et al. 2015

International Journal of Distributed Sensor Networks

Self Cite

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“…First, we classify the intensity distribution space into two categories; thus an image patch can be described with a label of one bit by classifying pixels in certain intensity level. Then, we establish the candidate target template only if the label of candidate target matches the label of reference target and adopt an improved particle filtering approach based on particle swarm optimization to track the selected image patch [12].…”

Section: Introductionmentioning

confidence: 99%

Fast Object Tracking Employing Labelled Particle Filter for Thermal Infrared Imager

Yang

Xia³

et al. 2015

International Journal of Distributed Sensor Networks

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More and more network cameras are now working over distributed networks, offering the capability of remote intelligent video surveillance. In this paper, we bring forward an original particle filter tracking algorithm named labelled particle filter which describes each image patch with a binary label. Based on the imaging theory of thermography, moving objects, such as pedestrians and automobiles, usually have higher intensities compared with the background in a gray-level pseudocolor mode. Thus an image patch can be classified into two categories according to its intensity distribution, and we can use a one-bit binary label, positive or negative, to describe the attribute of image patch. Therefore, the candidate target template is established only if the label of candidate target matches the label of reference target, and the computational complexity is reduced consequently. Experiments are conducted to show that the proposed algorithm can handle real-time object tracking with less time cost while maintaining high tracking accuracy.

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Cooperative Tracking Using Multiple PTZ Thermal Imagers

Cited by 2 publications

References 6 publications

Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

Fast Object Tracking Employing Labelled Particle Filter for Thermal Infrared Imager

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