![]() Design and development issues focused on CV integration to applications for CE devices, specifically applications involving the use of CV to detect the at home device selection by physical user pointing. This environment is widely understood through DLNA and UPnP technologies and use cases so product and open source technology was readily available for many actions - such as play/pause/skip media control of video over an IP network. To focus this study, reduce development risks, and make the application scenarios somewhat self explanatory, we consider networked multimedia devices at home as the target consumer environment. Thus, it is a timely point to consider whether CV is still an experimental and high-risk technology for CE, or whether it is becoming a commoditized component for easy integration. Although CV is more than 30 years old as a scientific and engineering discipline, it is only recently that large personal photo databases on modern PCs, and camera- smartphones with high performance computing architectures, have brought CV into the hands of consumers through face recognition and augmented reality map applications. ![]() ![]() CV applications span from real-time multi-view live video security threat detection to batch offline processing of large medical image repositories. INTRODUCTION Computer vision (CV) is the machine processing of imagery to determine what images and elements of images are meaningful within specific applications. Using OpenCV and the cross- platform Qt development environment, we investigate the suitability of an open building block approach for rapid concept prototyping of computer vision based user interaction designs in CE-orientated networked multimedia home environments. The increasing availability of open source implementations of computer vision algorithms promises to commoditize these technologies as reusable community maintained building blocks.
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