We describe an effective constituent projection strategy, where constituent projection is performed on the basis of dependency projection. Especially, a novel measurement is proposed to evaluate the candidate projected constituents for a target language sentence, and a PCFG-style parsing procedure is then used to search for the most probable projected constituent tree. Experiments show that, the parser trained on the projected treebank can significantly boost a state-of-the-art supervised parser. When integrated into a tree-based machine translation system, the projected parser leads to translation performance comparable with using a supervised parser trained on thousands of annotated trees. 1