Shot boundary detection (SBD) is regarded as one of the most criti cal issues in content-based video retrieval technology.The existing algorithms are sensitive to the motions caused by cameras and objects,and also need huge amount of computation.With regard to these disadvantages,a shot bounda ry detection algorithm based on compressive sensing and weighted major color (CSWMC) is proposed.Firstly,a c oarse set of shot boundaries is obtained by comparison of frames′ histogram features,then the high dimensio nal features of the frames in the set and their neighboring frames are projected to low dimensional space,and afte r that,the first decision criterion based on angle similarity is generated by the computation of adjusted cosine sim ilarity.Secondly,a novel weighted value for image major color is defined and applied to the calculation of a new B hattacharyya-like similarity,which is used as the second decision criterion ba sed on color similarity.Finally,the product of the two decision criteria is computed as the ultimate one.At the same time,a naive yet e ffective strategy is designed for boundary detection.The experimental results demonstrate that the proposed algor ithm has higher recall rate and precision rate,and could perform shot boundary detection more effectively than those state-of-the-art methods.