2018/03/19 by Silvia L. Pintea, Jan van Gemert, Jan C. van Gemert +5 · 1 citation
Computer Science · #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Video Analysis and Summarization #cs.CV
paper · pdf · doi:10.48550/arxiv.1803.06951
Published in the proceedings of the European Conference on Computer Vision (ECCV), 2014
openalex publication_date 2018/03/19 · arxiv created 2018/03/21 · arxiv updated 2018/03/22 · openalex created_date 2019/07/30 · openalex updated_date 2026/07/28
This paper proposes motion prediction in single still images by learning it from a set of videos. The building assumption is that similar motion is characterized by similar appearance. The proposed method learns local motion patterns given a specific appearance and adds the predicted motion in a number of applications. This work (i) introduces a novel method to predict motion from appearance in a single static image, (ii) to that end, extends of the Structured Random Forest with regression derived from first principles, and (iii) shows the value of adding motion predictions in different tasks such as: weak frame-proposals containing unexpected events, action recognition, motion saliency. Illustrative results indicate that motion prediction is not only feasible, but also provides valuable information for a number of applications.