If the sensor sample frequency and throughput is high, relative to target motion through the field of view (e.g. 25fps camera) then we can validly set such a temporal window to a value above the occurrence level of spurious false positive detections. This approach is illustrated using the example of automated real-time vehicle and people detection, in multi-modal visible (EO) and thermal (IR) imagery, deployed on an unattended dual-sensor pod. A sensitive target detection approach, based on a codebook mapping of visual features, classifies target regions initially extracted from the scene using an adaptive background model. The use of temporal filtering provides a consistent, fused onward information feed of targets detected from either or both sensors whilst minimizing the onward transmission of false positive detections and facilitating the use of an otherwise sensitive detection approaches within the robust target reporting context of a deployed sensor network. |
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CITATIONS
Cited by 2 scholarly publications.
Target detection
Sensors
Video
Image classification
Thermography
Video surveillance
Sensor networks