Charles E. Hughes

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The raw size of a high-dynamic-range (HDR) image brings about problems in storage and transmission. Many bytes are wasted in data redundancy and perceptually unimportant information. To address this problem, researchers have proposed some preliminary algorithms to compress the data, like RGBE/XYZE, OpenEXR, LogLuv, and so on. HDR images can have a dynamic(More)
A major goal for researchers in neuroevolution is to evolve artificial neural networks (ANNs) that can <i>learn</i> during their lifetime. Such networks can adapt to changes in their environment that evolution on its own cannot anticipate. However, a profound problem with evolving adaptive systems is that if the impact of learning on the fitness of the(More)
Biological brains can adapt and learn from past experience. Yet neuroevolution, i.e. automatically creating artificial neural networks (ANNs) through evolutionary algorithms, has sometimes focused on static ANNs that cannot change their weights during their lifetime. A profound problem with evolving adaptive systems is that learning to learn is highly(More)
Transferring research from the laboratory to mainstream applications requires the convergence of people, knowledge, and conventions from divergent disciplines. Solutions involve more than combining functional requirements and creative novelty. To transform technical capabilities of emerging mixed reality (MR) technology into the mainstream involves the(More)
Interactive evolutionary computation (IEC) has proven useful in a variety of applications by combining the subjective evaluation of a user with the massive parallel search power of the genetic algorithm (GA). Here, we articulate a framework for an extension of IEC into collaborative interactive evolution, in which multiple users guide the evolutionary(More)
Technology has advanced to the point where realism in virtual reality is very achievable. However, in our obsession to reproduce the world and human experience in virtual space, we overlook the most important aspects of what makes us who we are—our reality. Yet, it isn’t enough just to trick the eye or fool the body and mind. One must capture the(More)
In contrast to sequential computation, concurrent computation gives rise to parallel events. Efforts to translate the history of concurrent computations into sequential event traces result in the potential uncertainty of the observed order of these events. Loosely coupled distributed systems complicate this uncertainty even further by introducing the(More)
Augmented reality involves mixing captured video with rendered elements in real-time. For augmented reality to be effective in training and simulation applications, the computer generated components need to blend in well with the captured video. Straightforward compositing is not sufficient, since the chromatic content of video and rendered data may be very(More)