Incremental Learning for Visual Tracking

We recorded a sequence to demonstrate that our tracker performs well in outdoor environ- ment where lighting conditions change drastically. The video was acquired when a person walking underneath a trellis covered by vines. As shown in Figure 3, the cast shadow changes the appearance of the target face drastically. Furthermore, the combined pose and lighting variation with low frame rate makes the tracking task extremely difficult. Nev- ertheless, the results show that our tracker successfully follows the target accurately and robustly. Due to heavy shadows and drastic lighting change, other tracking methods based on gradient, contour, or color information are unlikely to perform well in this case.