Ergonomics-Inspired Reshaping and Exploration of Collections of Models

Zheng, Youyi; Liu, Han; Dorsey, Julie; Mitra, Niloy J.

doi:10.1109/tvcg.2015.2448084

Cited by 28 publications

(15 citation statements)

References 32 publications

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“…Earlier work in the animation community by Lee et al [LCL06] has proposed the “motion patches” representation which organizes geometric patches by analysis of motion captured pose data that interacts with the patch. Zheng et al [ZLDM16] demonstrate an efficient 3D object editing interface that connects deformations of the object geometry to the pose of a person interacting with the object through a set of ergonomics rules. Zhao et al [ZCK17] have proposed indexing of an IBS‐based representation of objects using a human pose in order to enable retrieval of human‐object interaction sequences from attributes of the pose.…”

Section: Geometry + Agent (Ga) Methodsmentioning

confidence: 99%

“…A prominent example in this group of work is the Shape2Pose system of Kim et al [KCGF14] which predicts interaction poses given the geometry of a specific instance for a known category of objects. The shape deformation interface of Zheng et al [ZLDM16] is designed to operate at the level of distinct objects such as benches or chairs. Similarly, the retrieval approach of Zhao et al [ZCK17] indexes single objects using the human poses that would be interacting with them.…”

Section: Geometry + Agent (Ga) Methodsmentioning

confidence: 99%

“…By relating global structure to functionality, Lun et al [LKWS16] automatically transfer the style of one shape to another with different functionalities via a sequence of element‐level operations. Finally, Zheng et al [ZLDM16] encode constraints relating the human pose with the part structure of chairs to allow for ergonomics‐inspired reshaping of the object geometry (see Figure ), while Fu et al [FCSF17] use human poses to guide part assembly and the synthesis of functional hybrid objects.…”

Section: Applicationsmentioning

confidence: 99%

“…The ergonomics‐based 3D object editing interface of Zheng et al [ZLDM16] allows for efficient editing and exploration of 3D chair designs that conform to the specified human pose configurations. The image is courtesy of Zheng et al [ZLDM16]. …”

Section: Applicationsmentioning

confidence: 99%

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Functionality Representations and Applications for Shape Analysis

Savva

Kaick

2018

Computer Graphics Forum

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A central goal of computer graphics is to provide tools for designing and simulating real or imagined artifacts. An understanding of functionality is important in enabling such modeling tools. Given that the majority of man‐made artifacts are designed to serve a certain function, the functionality of objects is often reflected by their geometry, the way that they are organized in an environment, and their interaction with other objects or agents. Thus, in recent years, a variety of methods in shape analysis have been developed to extract functional information about objects and scenes from these different types of cues. In this report, we discuss recent developments that incorporate functionality aspects into the analysis of 3D shapes and scenes. We provide a summary of the state‐of‐the‐art in this area, including a discussion of key ideas and an organized review of the relevant literature. More specifically, the report is structured around a general definition of functionality from which we derive criteria for classifying the body of prior work. This definition also facilitates a comparative view of methods for functionality analysis. We focus on studying the inference of functionality from a geometric perspective, and pose functionality analysis as a process involving both the geometry and interactions of a functional entity. In addition, we discuss a variety of applications that benefit from an analysis of functionality, and conclude the report with a discussion of current challenges and potential future works.

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Section: Geometry + Agent (Ga) Methodsmentioning

confidence: 99%

Section: Geometry + Agent (Ga) Methodsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

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Functionality Representations and Applications for Shape Analysis

Savva

Kaick

2018

Computer Graphics Forum

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“…The research of human body shape is one of the important research fields of ergonomics [1], which contains all kinds of information. In the field of clothing, body shape plays an important role as non-verbal information.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Body Size by Combining Genetic Algorithm with Human Body Model

Yadikar¹,

Zhang²,

Mamat³

et al. 2017

Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)

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Abstract-Estimation of body size using related dataset is one of the challenging tasks in modeling and simulation area. It has a wide range of utilization in many aspects in society including body modeling, designing clothes etc. It is necessary to extract feature data in body size measurement. Except ordinary data such as the body height, weight and chest size, the body surface area and volume were made up B-Spline surface shape model by linear combined with these data in this paper. Several control points were selected after using Genetic Algorithm (GA) to select best points in theses dataset, and mathematical model of estimating human body size was created. Experimental results indicated that this model has advantages of high efficiency and low error rates in estimating human body size.Keywords-genetic algorithm: GA; surface area; the control points of b-spline surface

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A Revisit of Shape Editing Techniques: From the Geometric to the Neural Viewpoint

Yuan

Lai

et al. 2021

J. Comput. Sci. Technol.

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3D shape editing is widely used in a range of applications such as movie production, computer games and computer aided design. It is also a popular research topic in computer graphics and computer vision. In past decades, researchers have developed a series of editing methods to make the editing process faster, more robust, and more reliable. Traditionally, the deformed shape is determined by the optimal transformation and weights for an energy formulation. With increasing availability of 3D shapes on the Internet, data-driven methods were proposed to improve the editing results. More recently as the deep neural networks became popular, many deep learning based editing methods have been developed in this field, which are naturally data-driven. We mainly survey recent research studies from the geometric viewpoint to those emerging neural deformation techniques and categorize them into organic shape editing methods and man-made model editing methods. Both traditional methods and recent neural network based methods are reviewed.

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Ergonomics-Inspired Reshaping and Exploration of Collections of Models

Cited by 28 publications

References 32 publications

Functionality Representations and Applications for Shape Analysis

Functionality Representations and Applications for Shape Analysis

Estimation of Body Size by Combining Genetic Algorithm with Human Body Model

A Revisit of Shape Editing Techniques: From the Geometric to the Neural Viewpoint

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