Video content identification using the Viterbi algorithm

We propose a video content identification that uses the Viterbi algorithm for identifying unknown video content from a database of reference content. Both the source video in the database and exact frame index therein of each query frame are determined by our method. The Viterbi algorithm is effective for enforcing temporal consistency over frame-level hypotheses based on matching frame fingerprints. We have introduced an “unknown” state in the Viterbi state model to handle both missed detections and non-existent matches. Another novelty of our approach is the use of frame time stamps for computing transition probabilities between frames. This makes our method capable of handling even extreme frame rate changes between query and reference videos. We have provided experimental results demonstrating the effectiveness of the proposed method. This approach may conceivably be used for audio content identification as well.