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We present an intuitive and efficient method for editing the appearance of complex spatially-varying datasets, such as images and measured materials. In our framework, users specify rough adjustments that are refined interactively by enforcing the policy that similar edits are applied to spatially-close regions of similar appearance. Rather than proposing a(More)
We compared face identification by humans and machines using images taken under a variety of uncontrolled illumination conditions in both indoor and outdoor settings. Natural variations in a person's day-to-day appearance (e.g., hair style, facial expression, hats, glasses, etc.) contributed to the difficulty of the task. Both humans and machines matched(More)
The intended applications of automatic face recognition systems include venues that vary widely in demographic diversity. Formal evaluations of algorithms do not commonly consider the effects of population diversity on performance. We document the effects of racial and gender demographics on estimates of the accuracy of algorithms that match identity in(More)
How does one recognize a person when face identification fails? Here, we show that people rely on the body but are unaware of doing so. State-of-the-art face-recognition algorithms were used to select images of people with almost no useful identity information in the face. Recognition of the face alone in these cases was near chance level, but recognition(More)
We propose a method for retargeting measured materials, where a source measured material is edited by applying the reflectance functions of a template measured dataset. The resulting dataset is a material that maintains the spatial patterns of the source dataset, while exhibiting the reflectance behaviors of the template. Compared to editing materials by(More)
We present an efficient approach that merges the virtual objects into video sequences taken by a freely moving camera in a realistic manner. The composition is visually and geometrically consistent through three main steps. First, a robust camera tracking algorithm based on key frames is proposed, which precisely recovers the focal length with a novel(More)
The neural organization of person processing relies on brain regions functionally selective for faces or bodies, with a subset of these regions preferring moving stimuli. Although the response properties of the individual areas are well established, less is known about the neural response to a whole person in a natural environment. Targeting an area of(More)
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