WebSumm: Plataforma Web para Configuração, Automação e Rastreabilidade de Sumarização Multivídeo
Resumo
Multi-video summarization selects complementary information from videos about the same topic, yet direct use of summarization engines scatters workflow configuration, execution metadata, and segment-level decisions. We present WebSumm, a web platform for composing reusable workflows and preserving execution provenance from the input collection and workflow version to criterion-level decisions and output artifacts. In 44 executions over 62 videos from 21 topics, WebSumm recovered the applied configuration in every run and persisted all 1,302 evaluations emitted by the engine; raising the redundancy threshold from 0.17 to 0.31 changed 2 of 42 decisions, each traced to its criterion, segment, and workflow version. A complementary protocol traversed all five stages twice for seven topics (21 videos and 202 supplied segments): 14/14 executions and database recoveries completed, and all 648 comparable actions matched. A one-command demonstration with three redistributable clips also produced a persisted Decision Log and a validated MP4. These results support configuration recovery, decision attribution, and operational repeatability in the observed cases, not summary quality or usability; code, media, documentation, and recorded results are available in a public artifact.
Referências
Tanveer Hussain, Khan Muhammad, Weiping Ding, Jaime Lloret, Sung Wook Baik, and Victor Hugo C. de Albuquerque. 2021. A Comprehensive Survey of Multi-View Video Summarization. Pattern Recognition 109 (2021), 107567. DOI: 10.1016/j.patcog.2020.107567
Ioannis Kontostathis, Evlampios Apostolidis, Konstantinos Apostolidis, and Vasileios Mezaris. 2025. Enhancing User Control in AI-Based Video Summarization for Social Media. In MultiMedia Modeling (MMM 2025). Springer Nature Singapore, Singapore, 119–126. DOI: 10.1007/978-981-96-2074-6_12
Guande Wu, Jianzhe Lin, and Claudio T. Silva. 2022. IntentVizor: Towards Generic Query Guided Interactive Video Summarization. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, New Orleans, LA, USA, 10493–10502. DOI: 10.1109/CVPR52688.2022.01025
