Realtime and robust object matching with a large number of templates

Most of conventional object matching methods are based on comparing local features, which are too computational demanding. Recently, Dominant Orientation Templates (DOT) were proposed to solve the efficiency issue. Although DOT obtains promising results, it still suffers the problem of wasting too many bits in representation and fragility when partial occlusion occurs. As the number of templates increase, the performance will decrease. Therefore, we propose a compact DOT representation with a fast partial occlusion handling approach. Instead of using seven orientations in the original implementation, we employ single orientation of the highest gradients for the proposed compact DOT representation (C-DOT). Consequently, the size of feature vectors is reduced from 8 bits to 3 bits. To efficiently tackle the partial occlusion, we introduce the C-DOT similarity map to store the matching scores of individual grids in each sliding window, which is used to further infer the occlusion map. The experimental results demonstrate that the proposed method outperforms DOT.