Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
From its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus,... more From its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus, Pointer (WIMP) user interface. WIMP has rarely been able to tap into the natural intuitiveness and imagination of the user which accompanies any design process. Brain-computer interface (BCI) is a novel modality that uses brain signals of a user to enable natural and intuitive interaction with an external device. BCI's potential to become an important modality of natural interaction for 3D modeling is almost limitless and unexplored. In theory, using BCI one can create any 3D model by just thinking about it. This paper presents a basic framework for using BCI as an interface for computer aided 3D modeling. This framework involves the task of recording and recognizing electroencephalogram (EEG) brain wave patterns and electromyogram (EMG) signals corresponding to facial movements. The recognized EEG/EMG brain signals and associated keystrokes are used to activate/control different commands of a CAD package. Eight sample CAD models created using the Emotiv EEG head set based BCI interface and Google SketchUp are presented to demonstrate the efficacy of the developed system based on the framework. To further exhibit BCI's usability, human factor studies have been carried out on subjects from different backgrounds. Based on preliminary results, it is concluded that EEG/EMG based BCI is suitable for computer aided 3D modeling purposes. Issues in signal acquisition, system flexibility, integration with other modalities and data collection are also discussed.
Volume 1A: 34th Computers and Information in Engineering Conference, 2014
ABSTRACT In this paper, 3D face recognition under isometric deformation (induced by facial expres... more ABSTRACT In this paper, 3D face recognition under isometric deformation (induced by facial expressions) is considered. The main objective is to employ the shape descriptors that are invariant to (isometric) deformations to provide an efficient face recognition algorithm. Two methods of the correspondence are utilized for automatic landmark assignment to the query face. One is based on the conventional iterative closest point (ICP) method and another is based upon the geometrical/topological features of the human face. The shape descriptor is chosen to be the well-known geodesic distance (GD) measure. The recognition task is performed on SHREC08 database for both correspondence methods and the effect of feature (GD) vector size as well as landmark positions on the recognition accuracy were argued.
Volume 1A: 34th Computers and Information in Engineering Conference, 2014
Additive manufacturing processes are capable of printing parts with any shape and complexity. The... more Additive manufacturing processes are capable of printing parts with any shape and complexity. The parts fabricated with additive manufacturing processes requires minimum human intervention. Process planning decisions play an important role in making sure the fabricated parts meets the desired specification, including the build time and cost. A quick and unified approach to quantify the manufacturing build time, accuracy, and cost in real time is lacking. In the present research, a generic and near real-time framework for unified additive manufacturing process planning is presented. We have developed computational geometric solutions to estimate tight upper bound of manufacturing process planning decisions that can be analyzed in almost real time. Results of developed computational approach are compared against the optimized process plans to ensure its applicability. Case studies comprising of numerous parts with varying shape, and application area is also outlined.
Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
The existing interfaces for 3D CAD modeling softwares use 2D subspace inputs such as x and y axes... more The existing interfaces for 3D CAD modeling softwares use 2D subspace inputs such as x and y axes of mouse to create 3D models. These existing interfaces are inherently modal because one needs to switch between subspaces, and disconnects the input space from modeling space. This makes existing interfaces tedious, complex, non-intuitive and difficult to learn. In this paper, a multi-sensory, interactive, and intuitive 3D CAD modeling interface is presented to address these shortcomings. Three different modalities (gestures, brain-computer interface, and speech) have been used for creating interactive and intuitive 3D CAD modeling interface. DepthSense® camera from SoftKinetic is used to recognize gestures, EEG Neuro-headset from Emotiv® is used for acquiring, and processing neuro-signals and CMU Sphinx is used for recognizing and processing speech. Multiple CAD models created by several users using the proposed multimodal interface are presented. In conclusion, the proposed system is easier to learn and use as compared to the already existing systems.
Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
The concepts of scale and platform based product family are being used by many companies to meet ... more The concepts of scale and platform based product family are being used by many companies to meet the customization needs of customers. Research in the area of product family design predominantly focuses on optimization frameworks. There is lack of creative conceptual computer aided 3D modeling tools for product family design exploration. In this paper, a gesture based conceptual computer aided design (C-CAD) exploration tool for scaled 3D product family models is presented. The proposed gesture based C-CAD allows for easy, natural, and intuitive modification of 3D objects to create scaled 3D product family models. The input 3D model for conceptual design exploration purposes are obtained in two ways, (a) 3D model is generated by scanning an existing product using depth sensing (RGB-D) camera, and (b) 3D models available in large online repository such as Google Warehouse and TurboSquid are used as-is. Hand gestures recognized using the DepthSense R 311 (RGB-D) camera from SoftKinetic R is used in conjunction with Principal Component Analysis (PCA) based geometric algorithms to enable the interactive scaling of inputted 3D models. The efficacy of the proposed method is demonstrated through multiple example problems. The proposed method of 3D model exploration is most * Address all correspondence to this author. useful for product designs that are scaled variants.
Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
From its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus,... more From its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus, Pointer (WIMP) user interface. WIMP has rarely been able to tap into the natural intuitiveness and imagination of the user which accompanies any design process. Brain-computer interface (BCI) is a novel modality that uses brain signals of a user to enable natural and intuitive interaction with an external device. BCI's potential to become an important modality of natural interaction for 3D modeling is almost limitless and unexplored. In theory, using BCI one can create any 3D model by just thinking about it. This paper presents a basic framework for using BCI as an interface for computer aided 3D modeling. This framework involves the task of recording and recognizing electroencephalogram (EEG) brain wave patterns and electromyogram (EMG) signals corresponding to facial movements. The recognized EEG/EMG brain signals and associated keystrokes are used to activate/control different commands of a CAD package. Eight sample CAD models created using the Emotiv EEG head set based BCI interface and Google SketchUp are presented to demonstrate the efficacy of the developed system based on the framework. To further exhibit BCI's usability, human factor studies have been carried out on subjects from different backgrounds. Based on preliminary results, it is concluded that EEG/EMG based BCI is suitable for computer aided 3D modeling purposes. Issues in signal acquisition, system flexibility, integration with other modalities and data collection are also discussed.
Volume 1A: 34th Computers and Information in Engineering Conference, 2014
ABSTRACT In this paper, 3D face recognition under isometric deformation (induced by facial expres... more ABSTRACT In this paper, 3D face recognition under isometric deformation (induced by facial expressions) is considered. The main objective is to employ the shape descriptors that are invariant to (isometric) deformations to provide an efficient face recognition algorithm. Two methods of the correspondence are utilized for automatic landmark assignment to the query face. One is based on the conventional iterative closest point (ICP) method and another is based upon the geometrical/topological features of the human face. The shape descriptor is chosen to be the well-known geodesic distance (GD) measure. The recognition task is performed on SHREC08 database for both correspondence methods and the effect of feature (GD) vector size as well as landmark positions on the recognition accuracy were argued.
Volume 1A: 34th Computers and Information in Engineering Conference, 2014
Additive manufacturing processes are capable of printing parts with any shape and complexity. The... more Additive manufacturing processes are capable of printing parts with any shape and complexity. The parts fabricated with additive manufacturing processes requires minimum human intervention. Process planning decisions play an important role in making sure the fabricated parts meets the desired specification, including the build time and cost. A quick and unified approach to quantify the manufacturing build time, accuracy, and cost in real time is lacking. In the present research, a generic and near real-time framework for unified additive manufacturing process planning is presented. We have developed computational geometric solutions to estimate tight upper bound of manufacturing process planning decisions that can be analyzed in almost real time. Results of developed computational approach are compared against the optimized process plans to ensure its applicability. Case studies comprising of numerous parts with varying shape, and application area is also outlined.
Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
The existing interfaces for 3D CAD modeling softwares use 2D subspace inputs such as x and y axes... more The existing interfaces for 3D CAD modeling softwares use 2D subspace inputs such as x and y axes of mouse to create 3D models. These existing interfaces are inherently modal because one needs to switch between subspaces, and disconnects the input space from modeling space. This makes existing interfaces tedious, complex, non-intuitive and difficult to learn. In this paper, a multi-sensory, interactive, and intuitive 3D CAD modeling interface is presented to address these shortcomings. Three different modalities (gestures, brain-computer interface, and speech) have been used for creating interactive and intuitive 3D CAD modeling interface. DepthSense® camera from SoftKinetic is used to recognize gestures, EEG Neuro-headset from Emotiv® is used for acquiring, and processing neuro-signals and CMU Sphinx is used for recognizing and processing speech. Multiple CAD models created by several users using the proposed multimodal interface are presented. In conclusion, the proposed system is easier to learn and use as compared to the already existing systems.
Volume 2A: 33rd Computers and Information in Engineering Conference, 2013
The concepts of scale and platform based product family are being used by many companies to meet ... more The concepts of scale and platform based product family are being used by many companies to meet the customization needs of customers. Research in the area of product family design predominantly focuses on optimization frameworks. There is lack of creative conceptual computer aided 3D modeling tools for product family design exploration. In this paper, a gesture based conceptual computer aided design (C-CAD) exploration tool for scaled 3D product family models is presented. The proposed gesture based C-CAD allows for easy, natural, and intuitive modification of 3D objects to create scaled 3D product family models. The input 3D model for conceptual design exploration purposes are obtained in two ways, (a) 3D model is generated by scanning an existing product using depth sensing (RGB-D) camera, and (b) 3D models available in large online repository such as Google Warehouse and TurboSquid are used as-is. Hand gestures recognized using the DepthSense R 311 (RGB-D) camera from SoftKinetic R is used in conjunction with Principal Component Analysis (PCA) based geometric algorithms to enable the interactive scaling of inputted 3D models. The efficacy of the proposed method is demonstrated through multiple example problems. The proposed method of 3D model exploration is most * Address all correspondence to this author. useful for product designs that are scaled variants.
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