VISIONE视频搜索系统：利用现有文本搜索引擎进行大规模视频检索
The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval
摘要：
在本文中，我们详细介绍了VISIONE，视频搜索系统，允许用户搜索视频使用文本关键字，发生的对象和它们的空间关系，发生的颜色和它们的空间关系，和图像相似性。这些模态可以组合在一起以表达复杂的查询并满足用户需求。我们的方法的特点是，我们编码的所有信息提取的关键帧，如视觉深度功能，标签，颜色和对象的位置，使用一个方便的文本编码索引在一个单一的文本检索引擎。这在必须合并与查询的各个部分（视觉、文本和位置）相对应的结果时提供了极大的灵活性。此外，我们报告了系统检索性能的广泛分析，使用视频浏览器摊牌（VBS）2019比赛期间生成的查询日志。这使我们能够通过在我们测试的参数和策略中选择最佳参数和策略来微调系统。
英文摘要：
In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships, and image similarity. These modalities can be combined together to express complex queries and satisfy user needs. The peculiarity of our approach is that we encode all the information extracted from the keyframes, such as visual deep features, tags, color and object locations, using a convenient textual encoding indexed in a single text retrieval engine. This offers great flexibility when results corresponding to various parts of the query (visual, text and locations) have to be merged. In addition, we report an extensive analysis of the system retrieval performance, using the query logs generated during the Video Browser Showdown (VBS) 2019 competition. This allowed us to fine-tune the system by choosing the optimal parameters and strategies among the ones that we tested.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
