Human Computer Interaction (HCI) is a fundamental issue for virtual reality environments due to the need for natural approaches and comfortable devices. Such goals can be achieved using hand gestures to interact with the virtual reality engine. This paper presents a real-time system based on hand gesture recognition (HGR) for interaction with CAVE applications. The whole pipeline can be roughly divided into four steps: segmentation, feature extraction for bag-of-features construction, classification through multiclass support vector machine (SVM), generation of commands to control the application. We build a grammar based on the hand gesture classes to convert the classification results in control commands for an application running in a CAVE. The input is the depth stream data acquired from a Kinect device. The hand gesture recognition and command generation/execution approaches compose a clientserver plugin that is part of a CAVE system implemented based on the InstantReality architecture and the X3D standard. The results show that the implemented plugin is a promising solution. We achieve suitable recognition accuracy and efficient object manipulation in a virtual room representing a surgical environment visualized in the CAVE.
The restoration and recovery of a defective skull can be performed through operative techniques to implant a customized prosthesis. Recently, image processing and surface reconstruction methods have been used for digital prosthesis design. In this paper we present a framework for prosthesis modeling. Firstly, we take the computed tomography (CT) of the skull and perform bone segmentation by thresholding. The obtained binary volume is processed by morphological operators, frame-by-frame, to get the inner and outer boundaries of the bone. These curves are used to initialize a 2D deformable model that generates the prosthesis boundary in each CT frame. In this way, we can fill the prosthesis volume which is the input for a marching cubes technique that computes the digital model of the target geometry. In the experimental results we demonstrate the potential of our technique and compare it with a related one.
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