A novel Siamese network object tracking algorithm based on tensor space mapping and memory-learning mechanism

•Build a correlation model of adjacent features to guide the feature update of subsequent states.•The updated features are fused with the template features to filter the discriminative attribute features.•Simulate the saccade mechanism to solve the problem of missing fine-grained features in batch information processing.•Filter fine-grained features by using hierarchical guidance and multiple traversals.