Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
J. Weibel, H. Li Tan, S. Lu:
"An Integrated Approach To Visual Attention Modelling Using Spatial-Temporal Saliency And Objectness";
Vortrag: IEEE Int. Conference on Image Processing (ICIP),
Beijing, China;
17.09.2017
- 20.09.2017; in: "Ieee Icip 2017",
(2017),
5 S.
Kurzfassung englisch:
Visual attention modelling is an important research
topic with a wide range of applications in visual tracking,
perceptual quality assessment, re-targeting, video summarization,
etc. In this paper, we propose a visual attention model that
captures both bottom-up spatial-temporal saliency and topdown
objectness. Leveraging on co-occurrence histograms, the
proposed model captures a number of low-level cues including
contrast, gradient, as well as, magnitude and gradient of optical
flow. Additionally, the proposed model incorporates mid-level
objectness cue which helps to boost the modelling performance
greatly. The proposed model obtained superior AUC-ROCs when
evaluated over the ASCMN dataset and the UCF Sports Action
dataset.
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.