000106635 001__ 106635 000106635 005__ 20211216131135.0 000106635 0247_ $$2doi$$a10.1109/CVPRW50498.2020.00528 000106635 0248_ $$2sideral$$a119935 000106635 037__ $$aART-2020-119935 000106635 041__ $$aeng 000106635 100__ $$0(orcid)0000-0001-8191-6261$$aBarbed, O.L.$$uUniversidad de Zaragoza 000106635 245__ $$aFine grained pointing recognition for natural drone guidance 000106635 260__ $$c2020 000106635 5060_ $$aAccess copy available to the general public$$fUnrestricted 000106635 5203_ $$aHuman action recognition systems are typically focused on identifying different actions, rather than fine grained variations of the same action. This work explores strategies to identify different pointing directions in order to build a natural interaction system to guide autonomous systems such as drones. Commanding a drone with hand-held panels or tablets is common practice but intuitive user-drone interfaces might have significant benefits. The system proposed in this work just requires the user to provide occasional high-level navigation commands by pointing the drone towards the desired motion direction. Due to the lack of data on these settings, we present a new benchmarking video dataset to validate our framework and facilitate future research on the area. Our results show good accuracy for pointing direction recognition, while running at interactive rates and exhibiting robustness to variability in user appearance, viewpoint, camera distance and scenery. 000106635 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FSE/T45-17R$$9info:eu-repo/grantAgreement/ES/MCIU-AEI-FEDER/PGC2018-096367-B-I00$$9info:eu-repo/grantAgreement/ES/MICIU-FEDER/PGC2018-098817-A-I00 000106635 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000106635 592__ $$a1.122$$b2020 000106635 593__ $$aElectrical and Electronic Engineering$$c2020 000106635 593__ $$aComputer Vision and Pattern Recognition$$c2020 000106635 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000106635 700__ $$0(orcid)0000-0002-3567-3294$$aAzagra, P.$$uUniversidad de Zaragoza 000106635 700__ $$aTeixeira, L. 000106635 700__ $$aChli, M. 000106635 700__ $$0(orcid)0000-0003-1368-1151$$aCivera, J.$$uUniversidad de Zaragoza 000106635 700__ $$0(orcid)0000-0002-7580-9037$$aMurillo, A.C.$$uUniversidad de Zaragoza 000106635 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000106635 773__ $$g2020-June (2020), 4480-4488$$pIEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. workshops$$tIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops$$x2160-7508 000106635 8564_ $$s2368922$$uhttps://zaguan.unizar.es/record/106635/files/texto_completo.pdf$$yPostprint 000106635 8564_ $$s2923128$$uhttps://zaguan.unizar.es/record/106635/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000106635 909CO $$ooai:zaguan.unizar.es:106635$$particulos$$pdriver 000106635 951__ $$a2021-12-16-13:04:48 000106635 980__ $$aARTICLE