Combining Shape and Color for Retrieval of 3D Models

Ruiz, Conrado; Cabredo, Rafael; Monteverde, Levi Jones C.; Huang, Zhiyoung

doi:10.1109/ncm.2009.140

Cited by 9 publications

(7 citation statements)

References 6 publications

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“…For 3D model retrieval applications, many state-of-the-art techniques are illustrated in [4], [5] and [21]. Shape is used as a basic feature to produce an efficient result for Bag-of-ViewWords.…”

Section: Related Workmentioning

confidence: 99%

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Visual Semantic Based 3D Video Retrieval System Using HDFS

Suguna²

2016

KSII TIIS

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This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose, we intent to hitch on BOVW and Mapreduce in 3D framework. Instead of conventional shape based local descriptors, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based-Predictive Clustering Tree) algorithm is used to generate visual codebook and histogram is produced. Further, matching is performed using soft weighting scheme with L 2 distance function. As a final step, retrieved results are ranked according to the Index value and acknowledged to the user as a feedback .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we future the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

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Section: Related Workmentioning

confidence: 99%

“…Combination of color and shape feature for 3D model is explained in [21]. Feature vector is used to map visual vocabulary to key point by counting the number of occurrences of the word in each sentence.…”

Section: Introductionmentioning

confidence: 99%

Visual Semantic Based 3D Video Retrieval System Using HDFS

Suguna²

2016

KSII TIIS

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“…For example, Suzuki et al [71] complemented the geometry description with a colour representation in terms of the Phong's model parameters [57]. Similarly, Ruiz et al [64] combined geometric similarity based on Shape Distributions [53] with colour similarity computed through the comparison of colour distribution histograms, while in Starck and Hilton [69] the colourimetric and the 3D shape information were concatenated into a histogram.…”

Section: Related Literaturementioning

confidence: 99%

“…The attention towards texture properties has grown considerably over the last few years, as demonstrated by the number of techniques for the analysis of geometric shape and texture attributes that have been recently proposed [33,46,54,64,75,80]. Since 2013, a retrieval contest [9] has been launched under the umbrella of the SHREC initiative [76] to evaluate the performances of the existing methods for 3D shape retrieval when dealing with textured models.…”

Section: Introductionmentioning

confidence: 99%

Retrieval and classification methods for textured 3D models: a comparative study

et al. 2015

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This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights in how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.

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“…This intriguing possibility has been considered in [26] where color information represented by the Phong's model parameters is used to assist in the retrieval process. Color and shape similarity are used together also in [27]. Here a shape simi-larity measure based on the method of [12] is combined with color similarity computed through the comparison of color distribution histograms.…”

Section: Related Workmentioning

confidence: 99%

Combining color and shape descriptors for 3D model retrieval

Pasqualotto

Zanuttigh

Cortelazzo

2013

Signal Processing: Image Communication

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Nowadays many three dimensional models feature color information together with the shape description. However current content-based retrieval schemes for 3D models are based on shape information only and ignore color clues. The significance of shape versus color clues for 3D model retrieval is instead a fundamental issue still almost unexplored at this time. A possible approach is to extend shape-based 3D model retrieval methods of proven effectiveness in order to include color. This work follows such rationale and introduces an extended version of the spin-image descriptor that can account also for color data. The comparison of color descriptors is performed using a novel scheme that allows to recognize as similar also objects with different colors but distributed in the same way over the shape. Shape and color similarity are finally combined together by an algorithm based on fuzzy logic. Experimental results show how the joint use of color and shape data allows to obtain better results than each of the two types of information alone. Comparisons with state-of-the-art content-based retrieval methods for 3D models also show how the proposed scheme outperforms standard solutions on object classes with meaningful color information.

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Combining Shape and Color for Retrieval of 3D Models

Cited by 9 publications

References 6 publications

Visual Semantic Based 3D Video Retrieval System Using HDFS

Visual Semantic Based 3D Video Retrieval System Using HDFS

Retrieval and classification methods for textured 3D models: a comparative study

Combining color and shape descriptors for 3D model retrieval

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