References

1. Danila Potapov, Matthijs Douze, Zaid Harchaoui, Cordelia Schmid. Category-Specific Video Summarization. ECCV 2014. — The paper that introduced KTS.

2. Zaid Harchaoui, Olivier Cappé. Retrospective Multiple Change-Point Estimation with Kernels. IEEE/SP SSP 2007. — The kernel change-point framework KTS builds on.

3. Ke Zhang, Wei-Lun Chao, Fei Sha, Kristen Grauman. Video Summarization with Long Short-Term Memory. ECCV 2016. — Popularized KTS as preprocessing for the TVSum / SumMe benchmarks.

Related ideas

• Dynamic programming for change-point detection — the same optimal-substructure recurrence appears in PELT, segmented regression, and ruptures-style libraries.
• The kernel trick — writing variance/distance purely through a Gram matrix is the same move behind kernel PCA and kernel k-means.

This book's code

• code/kts.py — the full implementation.
• code/demo.py — the synthetic-data demo.
• code/kts_video.py — one-file CLI tool for real videos.

Both depend only on NumPy (Matplotlib optional, for the demo plot).