Cross-correlation tracking technique for extracting speed from cameras under adverse conditions Schoepflin, Todd N ; Dailey, Daniel J
Publication details: Transportation Research Record, 2004Description: nr 1867, s. 36-45Subject(s): Bibl.nr: VTI P8167:1867; VTI P8169:2004Location: Abstract: An algorithm to estimate speed from traffic surveillance cameras in a variety of traffic congestion, weather, and lighting conditions is presented. The features from the images are projected into a one-dimensional subspace and transformed into a linear coordinate system by using a simplified camera model. A cross-correlation technique is used to summarize the movement of features through a group of images and to estimate mean speed for each lane of vehicles. A Kalman filter technique with a set of maximum-likelihood optimal parameters is used to estimate the traffic speed by lane to create optimal space-average speed.| Current library | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|
| Statens väg- och transportforskningsinstitut | Available | ||||
| Statens väg- och transportforskningsinstitut | Available |
An algorithm to estimate speed from traffic surveillance cameras in a variety of traffic congestion, weather, and lighting conditions is presented. The features from the images are projected into a one-dimensional subspace and transformed into a linear coordinate system by using a simplified camera model. A cross-correlation technique is used to summarize the movement of features through a group of images and to estimate mean speed for each lane of vehicles. A Kalman filter technique with a set of maximum-likelihood optimal parameters is used to estimate the traffic speed by lane to create optimal space-average speed.