A temporal feature vector which is robust against aspect ratio variations

Motion vectors histogram (MVH) is an effective feature vector in video indexing and analysis applications. One of the challenges in the use of motion vector histogram is that it is not robust to video aspect ratio (AR). As a result, it is not suitable for comparing videos with different ARs. In this paper a feature vector based on motion vectors in H.264/AVC is introduced which is robust to variations in aspect ratio. This feature vector, namely scaled motion vector histogram (SMVH), has superior performance compared to common MVH and experimental results indicates that SMVH achieves on average 10% improvement in similarity detection of videos with different ARs compared with MVH.