Dense Trajectories and Motion Boundary Descriptors for Action Recognition

• Published in: International journal of computer vision Vol. 103; no. 1; pp. 60 - 79
• Main Authors: Wang, Heng, Kläser, Alexander, Schmid, Cordelia, Liu, Cheng-Lin
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.05.2013; Springer; Springer Nature B.V; Springer Verlag
• Subjects: Algorithms; Analysis; Applied sciences; Artificial Intelligence; Boundaries; Cameras; Classification; Computer Imaging; Computer Science; Computer science; control theory; systems; Computer Vision and Pattern Recognition; Datasets; Exact sciences and technology; Histograms; Image Processing and Computer Vision; Image processing systems; Pattern Recognition; Pattern Recognition and Graphics; Pattern recognition. Digital image processing. Computational geometry; Recognition; Representations; Sensors; Spacetime; State of the art; Studies; Trajectories; Vision; Vision systems; Action recognition; Motion boundary histograms; Dense trajectories; Multimedia; Computer vision; Action; Histogram; Motion estimation; Point shape; Video signal; Mobility; Sport; Behavioral analysis; Scene analysis; Classification; Object detection; Trajectory; Web site; Pattern extraction; Optical flow

This paper introduces a video representation based on dense trajectories and motion boundary descriptors. Trajectories capture the local motion information of the video. A dense representation guarantees a good coverage of foreground motion as well as of the surrounding context. A state-of-the-art o...