In addition to optical flow-based approaches, several other motion-based cues or representations can be explored to complement the event boundary detection process. One potential cue is motion energy, which quantifies the overall movement in a video segment. By analyzing the distribution of motion energy across frames, the algorithm can identify segments with significant motion changes, indicating potential event boundaries. Another cue is motion directionality, which captures the direction of movement in the video. By analyzing the consistency and changes in motion direction, the algorithm can detect transitions between different actions or scenes, leading to more accurate event boundary detection. Furthermore, exploring motion coherence, which measures the consistency of motion patterns within a video segment, can help identify coherent events and boundaries. By integrating these additional motion cues with optical flow-based approaches, the algorithm can enhance its robustness and accuracy in detecting event boundaries.