Because of the complicated optical environment underwater and the moving target characteristics

it is difficult to extract target features and predict target sizes precisely in underwater videos.Thus

tracking window offsets become bigger and cannot envelop the target area accurately during the target tracking process.A novel approach of visual depth based target feature calculation and target tracking is therefore presented.First

visual depth information is calculated by dark channel prior

thus the target's spatial position feature is extracted.Second

dehazing and color restoration of the underwater image is applied based on the depth information and the target's feature will be enhanced.At last

an underwater target is tracked under the Bayesian filter framework.Meanwhile

the target window size is adaptively adjusted based on the target's spatial position feature.Experimental results show that the proposed algorithm can calculate target features and optimize tracking windows based on the visual depth.Thus

objects can be tracked adaptively.This paper presents a new underwater targets tracking method based on the calculation of visual depth information.Experimental results validate its robustness in underwater target adaptive tracking. Furthermore

it can be used in various nonlinear non-Gaussian underwater target-tracking frameworks.