Fast approximate convex decomposition using relative concavity

Ghosh, Mukulika; Amato, Nancy M.; Lü, Yanyan; Lien, Jyh-Ming

doi:10.1016/j.cad.2012.10.032

Cited by 50 publications

(28 citation statements)

References 26 publications

(47 reference statements)

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“…Box2D [8] is used as the physics engine. For performance, parts are simplified using polyline optimization and approximate convex decomposition [12]. We support a variety of input methods, traditional mouse, pen, and single-hand multitouch.…”

Section: Methodsmentioning

confidence: 99%

PacCAM

Saakes

Cambazard

Mitani

et al. 2013

Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology

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Figure 1. PacCAM supports users in packing 2D parts by capturing materials in a CNC machine (a) and using the captured materials (b) in a dedicated user interface based on 2D rigid body simulation and snapping (c), resulting in optimized utilization of material for efficient fabrication (d). ABSTRACTThe availability of low-cost digital fabrication devices enables new groups of users to participate in the design and fabrication of things. However, software to assist in the transition from design to actual fabrication is currently overlooked. In this paper, we introduce PacCAM, a system for packing 2D parts within a given source material for fabrication using 2D cutting machines. Our solution combines computer vision to capture the source material shape with a user interface that incorporates 2D rigid body simulation and snapping. A user study demonstrated that participants could make layouts faster with our system compared with using traditional drafting tools. PacCAM caters to a variety of 2D fabrication applications and can contribute to the reduction of material waste.

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Section: Methodsmentioning

confidence: 99%

PacCAM

Saakes

Cambazard

Mitani

et al. 2013

Proceedings of the 26th Annual ACM Symposium on User Interface Software and Technology

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“…Similarly, Ghosh et al . [GALL13] proposed a fast approximate convex decomposition (FACD) in order to comply with the quality of the partitioning of an object into approximately convex components. The quality is related to the increasing of naturalness and the minimization of redundancy of components (i.e.…”

Section: Volume‐based Segmentationmentioning

confidence: 99%

Part‐Based Mesh Segmentation: A Survey

Rodrigues

Morgado

Gomes

2018

Computer Graphics Forum

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This paper surveys mesh segmentation techniques and algorithms, with a focus on part‐based segmentation, that is, segmentation that divides a mesh (featuring a 3D object) into meaningful parts. Part‐based segmentation applies to a single object and also to a family of objects (i.e. co‐segmentation). However, we shall not address here chart‐based segmentation, though some mesh co‐segmentation methods employ such chart‐based segmentation in the initial step of their pipeline. Finally, the taxonomy proposed in this paper is new in the sense that one classifies each segmentation algorithm regarding the dimension (i.e. 1D, 2D and 3D) of the representation of object parts. The leading idea behind this survey is to identify the properties and limitations of the state‐of‐the‐art algorithms to shed light on the challenges for future work.

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“…It is usually regarded as an optimization problem that divides the network while minimizing or maximizing some given criteria or property in the computational geometry. Most of these problems are, however, known to be NP-hard [15].…”

Section: B Network Partitioningmentioning

confidence: 99%

“…Approximate convex decomposition (ACD) aims at minimizing concavity along with obtaining balanced partitions with perceivable components [19]. Wan [20] extends ACD to incorporate both concavity and curvature and prevents over-segmentation by avoiding cuts inside pockets.…”

Section: B Network Partitioningmentioning

confidence: 99%

DisLoc: A Convex Partitioning Based Approach for Distributed 3-D Localization in Wireless Sensor Networks

Fan

Luan

et al. 2017

IEEE Sensors J.

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Abstract-Accurate localization in wireless sensor networks (WSNs) is fundamental to many applications, such as geographic routing and position-aware data processing. This, however, is challenging in large scale 3D WSNs due to the irregular topology, such as holes in the path, of the network. The irregular topology may cause overestimated Euclidean distance between nodes as the communication path is bent, and accordingly introduces severe errors in 3D WSN localization. As an effort towards the issue, this work develops a distributed algorithm to achieve accurate 3D WSN localization. Our proposal is composed of two steps, segmentation and joint-localization. In specific, the entire network is first divided into several subnetworks by applying the approximate convex partitioning. A spatial convex node recognition mechanism is developed to assist the network segmentation which relies on the connectivity information only. After that, each subnetwork is accurately localized by using the multi-dimensional scaling (MDS) based algorithm. The proposed localization algorithm also applies a new 3D coordinate transformation algorithm, which helps reduce the errors introduced by coordinate integration between subnetworks and improve the localization accuracy. Using extensive simulations, we show that our proposal can effectively segment a complex 3D sensor network and significantly improve the localization rate in comparison with existing solutions.

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Fast approximate convex decomposition using relative concavity

Cited by 50 publications

References 26 publications

PacCAM

PacCAM

Part‐Based Mesh Segmentation: A Survey

DisLoc: A Convex Partitioning Based Approach for Distributed 3-D Localization in Wireless Sensor Networks

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