Pregled bibliografske jedinice broj: 1047292
Object recognition based on convex hull alignment
Object recognition based on convex hull alignment // Pattern recognition, 102 (2020), 107199, 19 doi:10.1016/j.patcog.2020.107199 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1047292 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Object recognition based on convex hull alignment
Autori
Cupec, Robert ; Vidović, Ivan ; Filko, Damir ; Đurović, Petra
Izvornik
Pattern recognition (0031-3203) 102
(2020);
107199, 19
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Object recognition ; Shape instance detection ; Depth image analysis ; Convex hull ; Shape alignment
Sažetak
A common approach to recognition of objects in cluttered scenes is to generate hypotheses about objects present in the scene by matching local descriptors of point features. These hypotheses are then evaluated by measuring how well they explain a particular part of the scene. In this paper, we investigate an alternative approach, which is based on alignment of convex hulls of segments detected in a depth image with convex hulls of target 3D object models or their parts. This alignment is performed using the Convex Template Instance descriptor. This descriptor was originally proposed for fruit recognition and classification of segmented objects. We have adapted this approach to recognize objects in complex scenes. Furthermore, we propose a novel three-level hypothesis evaluation strategy which can be used to achieve highly efficient object recognition. The proposed approach is evaluated by comparison with nine state-of-the- art approaches using three challenging benchmark datasets.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2014-09-3155 - Napredna 3D percepcija za mobilne robotske manipulatore (ARP3D) (Cupec, Robert, HRZZ - 2014-09) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus