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—We propose a content-aware stereoscopic image display adaptation method which simultaneously resizes a binocular image to the target resolution and adapts its depth to the comfort zone of the display while preserving the perceived shapes of prominent objects. This method does not require depth information or dense correspondences. Given the specification(More)
This paper proposes a novel parametric warp which is a spatial combination of a projective transformation and a similarity transformation. Given the projective transformation relating two input images, based on an analysis of the projective transformation, our method smoothly extrapolates the projective transformation of the overlapping regions into the(More)
The difficulty of vision-based posture estimation is greatly decreased with the aid of commercial depth camera, such as Microsoft Kinect. However, there is still much to do to bridge the results of human posture estimation and the understanding of human movements. Human movement assessment is an important technique for exercise learning in the field of(More)
With the aid of depth camera, such as Microsoft Kinect, the difficulty of vision-based posture estimation is greatly decreased, and human action analysis has achieved a wide range of applications. However, there is still much to do to develop effective movement assessment technique, which bridges the results of human posture estimation and the understanding(More)
This paper proposes a new projection model for mapping a hemisphere to a plane. Such a model can be useful for viewing wide-angle images. Our model consists of two steps. In the first step, the hemisphere is projected onto a swung surface constructed by a circular profile and a rounded rectangular trajectory. The second step maps the projected image on the(More)
We propose a content-aware stereoscopic image display adaptation method which simultaneously resizes a binocular image to the target resolution and adapts its depth to the comfort zone of the display while preserving the perceived shapes of prominent objects [Chang et al. 2011]. This method does not require depth information or dense correspondences. Given(More)
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