Saliency Based Detection for Maritime Object Tracking
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.
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)