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Saliency-based detection for maritime object tracking

Cane, T. and Ferryman, J. (2016) Saliency-based detection for maritime object tracking. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 26 June-1 July 2016, Las Vegas, USA, pp. 1257-1264.

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This paper presents a new method for object detection and tracking based on visual saliency as a way of mitigating against challenges present in maritime environments. Object detection is based on adaptive hysteresis thresholding of a saliency map generated with a modified version of the Boolean Map Saliency (BMS) approach. We show that the modification reduces false positives by suppressing detection of wakes and surface glint. Tracking is performed by matching detections frame to frame and smoothing trajectories with a Kalman filter. The proposed approach is evaluated on the PETS 2016 challenge dataset on detecting and tracking boats around a vessel at sea.

Item Type:Conference or Workshop Item (Paper)
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:68994

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