A Drone Video Clip Dataset and its Applications in Automated Cinematography

Drones became popular video capturing tools. Drone videos in the wild are first captured and then edited by humans to contain aesthetically pleasing camera motions and scenes. Therefore, edited drone videos have extremely useful information for cinematography and for applications such as camera path planning to capture aesthetically pleasing shots. To design intelligent camera path planners, learning drone camera motions from these edited videos is essential. However, first, this requires to filter drone clips and extract their camera motions out of these edited videos that commonly contain both drone and non-drone content. Moreover, existing video search engines return the whole edited video as a semantic search result and cannot return only drone clips inside an edited video. To address this problem, we proposed the first approach that can automatically retrieve drone clips from an unlabeled video collection using high-level search queries, such as drone clips captured outdoor in daytime from rural places. The retrieved clips also contain camera motions, camera view, and 3D reconstruction of a scene that can help develop intelligent camera path planners. To train our approach, we needed numerous examples of edited drone videos. To this end, we introduced the first large-scale dataset composed of edited drone videos. This dataset is also used for training and validating our drone video filtering algorithm. Both quantitative and qualitative evaluations have confirmed the validity of our method.

Automated summary

Drones have become popular in video capturing, and edited drone videos provide valuable information for cinematography and camera path planning. However, filtering drone clips and extracting camera motions from edited videos is challenging, and existing video search engines cannot accurately return only drone clips. To address this, the proposed approach automatically retrieves drone clips from unlabeled videos based on high-level search queries and introduces a large-scale dataset of edited drone videos for training and validation.