How well current saliency prediction models perform on UAVs videos? - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2019

How well current saliency prediction models perform on UAVs videos?

Abstract

It is exciting to witness the fast development of Unmanned Aerial Vehicle (UAV) imaging which opens the door to many new applications. In view of developing rich and efficient services, we wondered which strategy should be adopted to predict salience in UAV videos. To that end, we introduce here a benchmark of off-the-shelf state-of-the-art models for saliency prediction. This benchmark studies comprehensively two challenging aspects related to salience, namely the peculiar characteristics of UAV contents and the temporal dimension of videos. This paper enables to identify the strengths and weaknesses of current static, dynamic, supervised and unsupervised models for drone videos. Eventually, we highlight several strategies for the development of visual attention in UAV videos.
Fichier principal
Vignette du fichier
CAIP_2019_BenchmarkDatsetEyeTrackUAV1(2).pdf (7.01 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02265047 , version 1 (08-08-2019)

Identifiers

Cite

Anne-Flore Perrin, Lu Zhang, Olivier Le Meur. How well current saliency prediction models perform on UAVs videos?. CAIP (International Conference on Computer Analysis of Images and Patterns), Sep 2019, Salermo, Italy. ⟨10.1007/978-3-030-29888-3_25⟩. ⟨hal-02265047⟩
138 View
319 Download

Altmetric

Share

Gmail Facebook X LinkedIn More