Traditional methods for Content-based Object Retrieval usually employ extracting and comparing local features

which are too computational demanding and require offline training process. Therefore

a novel real-time CBOR method based on dominant orientation templates (DOT) is proposed. Besides

the proposed method makes use of the spatial distributions of grid scores to construct likelihood maps and utilizes a pyramid-scoring strategy to dispose the false windows in which the grid scores are dispersed. With the above improvement

the implementation for CBOR is able to retrieve the query target directly from the videos without offline training. The results show the proposed method improves the retrieval performance while retaining real-time processing ability of DOT matching.