IEEE Trans Image Process - A novel approach to FRUC using discriminant saliency and frame segmentation.

Tópicos

{ motion(1329) object(1292) video(1091) }
{ imag(2675) segment(2577) method(1081) }
{ featur(3375) classif(2383) classifi(1994) }
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{ detect(2391) sensit(1101) algorithm(908) }
{ can(774) often(719) complex(702) }
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Resumo

Motion-compensated frame interpolation (MCFI) is a technique used extensively for increasing the temporal frequency of a video sequence. In order to obtain a high quality interpolation, the motion field between frames must be well-estimated. However, many current techniques for determining the motion are prone to errors in occlusion regions, as well as regions with repetitive structure. We propose an algorithm for improving both the objective and subjective quality of MCFI by refining the motion vector field. We first utilize a discriminant saliency classifier to determine which regions of the motion field are most important to a human observer. These regions are refined using a multistage motion vector refinement (MVR), which promotes motion vector candidates based upon their likelihood given a local neighborhood. For regions which fall below the saliency-threshold, a frame segmentation is used to locate regions of homogeneous color and texture via normalized cuts. Motion vectors are promoted such that each homogeneous region has a consistent motion. Experimental results demonstrate an improvement over previous frame rate up-conversion (FRUC) methods in both objective and subjective picture quality.

Resumo Limpo

motioncompens frame interpol mcfi techniqu use extens increas tempor frequenc video sequenc order obtain high qualiti interpol motion field frame must wellestim howev mani current techniqu determin motion prone error occlus region well region repetit structur propos algorithm improv object subject qualiti mcfi refin motion vector field first util discrimin salienc classifi determin region motion field import human observ region refin use multistag motion vector refin mvr promot motion vector candid base upon likelihood given local neighborhood region fall saliencythreshold frame segment use locat region homogen color textur via normal cut motion vector promot homogen region consist motion experiment result demonstr improv previous frame rate upconvers fruc method object subject pictur qualiti

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