Object tracking with temporal prediction and spatial refinement (TPSR)

• A robust tracker based on temporal prediction and spatial refinement is proposed.
• Temporal prediction relies on two complementary components.
• Fine-tuning using the local spatial information avoids the error drifting.

A temporal prediction and spatial refinement (TPSR) method for online single object tracking (SOT) is proposed in this work. The TPSR tracking system consists of three cascaded modules: pre-processing (PP), temporal prediction (TP) and spatial refinement (SR). Illumination variation and shaking camera movement are two challenging factors in the tracking problem. They are first compensated in the PP module. Then, a joint region-based template matching (TM) and pixel-wised optical flow (OF) scheme is adopted in the TP module, where the switch between TM and OF is conducted automatically. These two modes work in a complementary manner to handle different foreground and background situations. Finally, to overcome the drifting error arising from the TP module, the bounding box location and size are finetuned using the local spatial information of the new frame in the SR module. The proposed TPSR tracking system offers the state-of-the-art performance with respect to a commonly used benchmarking dataset.