Modeling 3D objects in domains like Computer Aided Design (CAD) is time-consuming and comes with a steep learning curve needed to master the design process as well as tool complexities. In order to simplify the modeling process, we designed and implemented a prototypical system that leverages the strengths of Virtual Reality (VR) hand gesture recognition in combination with the expressiveness of a voice-based interface for the task of 3D modeling. Furthermore, we use the Constructive Solid Geometry (CSG) tree representation for 3D models within the VR environment to let the user manipulate objects from the ground up, giving an intuitive understanding of how the underlying basic shapes connect. The system uses standard mid-air 3D object manipulation techniques and adds a set of voice commands to help mitigate the deficiencies of current hand gesture recognition techniques. A user study was conducted to evaluate the proposed prototype. The combination of our hybrid input paradigm shows to be a promising step towards easier to use CAD modeling.
Multimodal Affect Analysis for Product Feedback Assessment
MIE, LSU（路易斯安那州立大学机械与工业工程系）
消费者经常对食品样品、香水、珠宝、太阳镜和服装配件等产品做出富有表现力的反应。本研究讨论了一个多模态的影响识别系统开发分类消费者是否喜欢或不喜欢的产品测试在柜台或售货亭，通过分析消费者的面部表情，身体姿势，手势，和语音测试后的产品。使用了一个具有深度功能的摄像头和麦克风系统- Kinect for Windows。一个情感识别引擎已被开发来分析图像和语音，以确定客户的情感状态。利用肤色和自适应阈值对图像进行分割。使用Haar级联分类器检测面部、身体和手。Canny边缘识别和嘴唇，身体和手的轮廓提取使用空间滤波。嘴、脸颊、眼睛、肩膀、手指周围的边数和方向以及边的位置被用作特征。通过情感模板映射算法和使用支持向量机训练分类器来完成分类。评价了反馈评价中多模态情感识别的实时性、准确性和可行性。
