Range Scans based 3D Shape Retrieval

Godil, Afzal; Dutağacı, Helin; Bustos, Benjamín; Choi, Seungjin; Dong, Shuilong; Furuya, Takahiko; Li, H.; Link, Norman; Moriyama, Ayane; Meruane, R.; Ohbuchi, R.; Paulus, Dietrich; Schreck, Tobias; Seib, Viktor; Sipiran, Ivan; Yin, Huanpu; Zhang, C.

doi:10.2312/3dor.20151069

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…One specific example is work by Sfikas et al [48], where the Authors used the PANORAMA descriptor [36] for matching parts of archaeological to complete objects. More recently, Tashiro et al [24] proposed a pipeline relying extensively on the SURF [6] local feature descriptor.…”

Section: Partial Object Retrievalmentioning

confidence: 99%

“…There exist many circumstances in which it is desirable to determine which larger object a smaller surface patch belongs to; occlusions and missing parts can result in this problem. This problem is known as Partial 3D Object Retrieval, and a number of methods have been proposed to date which address it [24] [30] [44] and finds application in areas such as archaeology [48] [20].…”

Section: Introductionmentioning

confidence: 99%

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Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing

van Blokland,

Theoharis

2021

Preprint

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A complete pipeline is presented for accurate and efficient partial 3D object retrieval based on Quick Intersection Count Change Image (QUICCI) binary local descriptors and a novel indexing tree. It is shown how a modification to the QUICCI query descriptor makes it ideal for partial retrieval. An indexing structure called Dissimilarity Tree is proposed which can significantly accelerate searching the large space of local descriptors; this is applicable to QUICCI and other binary descriptors. The index exploits the distribution of bits within descriptors for efficient retrieval. The retrieval pipeline is tested on the artificial part of SHREC'16 dataset with near-ideal retrieval results.

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