We propose an efficient technique for temporally aligning video sequences of similar activities. The proposed technique is able to synchronize view-variance videos from different scenes performing similar 3-D activities. Unlike existing techniques that just consider unidirectional alignment, the proposed technique considers symmetric temporal alignment and computes the optimal alignment by eliminating any view-based bias. The advantages of our technique are validated by experiments conducted on synthetic and real video data. The experimental results show that the proposed technique out-performs existing techniques in several test video sequences.