Unified Approach to Detection and Identification of Commercial Films by Temporal Occurrence Pattern

In this paper, we propose a method to detect and identify commercial films from broadcast videos by using Temporal Occurrence Pattern (TOP). Our method uses the characteristic of broadcast videos in Japan that each individual commercial film appears multiple times in broadcast stream and typically has the same duration (e.g., 15 seconds). Using this characteristic, the method can detect as well as identify individual commercial films within given video archive. Based on simple signature (global feature) for each frame image, the method first puts all frames into numbers of buckets where each bucket contains frames having the same signature, and thus they appear the same. For each bucket, TOP as a binary sequence representing the occurrence time within video archive is then generated. All buckets are then clustered using simple hierarchical clustering with similarity between TOPs allowing possible temporal offset. This clustering stage can stitch up all frames for each commercial film and identify multiple occurrence of the same commercial film at the same time. We tested our method using actual broadcast video archive and confirmed good performance in detecting and identifying commercial films.