Prediction based occluded multitarget tracking using spatio-temporal attention

This paper proposes the prediction based occluded multitarget tracking method using spatio-temporal attention mechanism. To cope with occlusion between targets, the proposed method provides an efficient method for more complex analysis by combining object association with partial probability model in spatially attentive window and occlusion activity detection in predicted temporal location. While multiple objects are moving or occluding between them in areas of visual field, a simultaneous tracking of multiple objects tends to fail. This is due to the fact that incompletely estimated feature vectors such as location, color, velocity, and acceleration of a target can provide only ambiguous and missing information. Thus, the spatially and temporally considered mechanism is proposed to track each target before, during, and after occlusion. Robustness of the proposed method is demonstrated with representative simulations.