Dual-Space Decomposition of 2D Complex Shapes

Liu, Guilin; Xi, Zhonghua; Lien, Jyh-Ming

doi:10.1109/cvpr.2014.529

Cited by 19 publications

(21 citation statements)

References 26 publications

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“…[11] is close to satisfy our constraints. In fact, the results of the DuDe [11] solution are more efficient comparing to those of the other algorithms. DuDe is a binary linear method to decompose complex shapes with an important number and different sizes of holes.…”

Section: Convex Decompositionsupporting

confidence: 52%

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Novel Method to Generate and Optimize Reticulated Structures of a Non Convex Conception Domain

Bialleten¹,

Chiheb²,

Afia³

et al. 2017

IJSEIA

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Reticulated structures are increasingly represented in industry. They are lighter than traditional structures which allows weight saving. So they can be the best choice when material gain offsets the production cost which is an optimization purpose.In this paper, we propose an algorithm to generate automatically a reticulated structure. We particularly study non-convex conception domains which can be decomposed into a finite number of convex sub-domains, specially polygons. This solution generates a structure with an optimum form based on an algorithm that works on convex design domains.

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Section: Convex Decompositionsupporting

confidence: 52%

“…To achieve our goal, we first determined the candidate algorithms to meet our constraints [6,[9][10][11]. We have developed a comparative study to choose the best algorithm from those selected.…”

Section: Convex Decompositionmentioning

confidence: 99%

Novel Method to Generate and Optimize Reticulated Structures of a Non Convex Conception Domain

Bialleten¹,

Chiheb²,

Afia³

et al. 2017

IJSEIA

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“…Based on this simple fact, a variety of part-related measures and decomposition methods mimicking human decomposition have been proposed in literature. [4][5][6][7][8][9][10][11][12][13][14][15] In the study of psychophysics, the short-cut rule 16 and the minima rule 17 have been suggested to understand the shape segmentation process of the human visual system. The short-cut rule points out that the human visual system prefers to partition a shape into parts using shorter cuts when other conditions are equal.…”

Section: Introductionmentioning

confidence: 99%

A coarse‐to‐fine shape decomposition based on critical points

et al. 2017

Concurrency and Computation

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Summary The segmentation of a shape into a series of meaningful parts is a fundamental problem in shape analysis and part‐based object representation. However, it is difficult to make the result of shape segmentation accord with the expectations of humans performing the same task. There is still a need for an effective way to segment the shape although a variety of methods have been proposed. In this paper, we present a novel shape decomposition algorithm, which is implemented in a coarse‐to‐fine manner, taking into account the critical points on the silhouette. First, a part‐cut hypotheses candidate set is generated and classified into 2 categories. Then, the hypotheses with adjacent endpoints are determined first, and later, the other kinds of hypotheses are finely determined by our presented measures such as chord arc ratio and inner angle. We note that the proposed coarse‐to‐fine decomposition conforms to the mechanism of human vision. The extensive experimental results on a large set of shapes show that our algorithm can generate shape decomposition results that better accord with human intuition compared to competing algorithms.

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“…Therefore, the segmentation method can be the combination of existing graphics decomposition algorithms and manually adjusting boundaries of these sub-domains. First, we initially divide the domain into several sub-domains by referring to polygon convex decomposition algorithms [24,25] and other relevant graphics decomposition algorithms [26][27][28]. Considering metric convexity is given by the ratio of the area of divided graphics to the area of convex hull, the ratio of the area of divided graphics to the area of circumscribed circle can be used if the divided graph be approaching round.…”

Section: D Pocketmentioning

confidence: 99%