Solving occlusion in Frame-Rate up-Conversion

Bellers, Erwin B.; Gurp, J.W. van; Janssen, J.G.W.M.; Braspenning, J.R.; Wittebrood, R.B.

doi:10.1109/icce.2007.341494

Cited by 26 publications

(14 citation statements)

References 7 publications

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“…three-step-search (TSS) [16], one-at-a-time-search search (OTS) [17], diamond search (DS) [18] and hexagonbased-search (HEXBS) [19], as well as algorithms based on spatio-temporal predictors, i.e. the predictive (zonal) search methods MVFAST [20] and EPZS [21], the RS methods 3DRS [3], HRNM [14] and TCSBP [1], and combined hierarchical-predictive methods, i.e. the MRSTmethod proposed in [22] and MPMVP from [4].…”

Section: Discussion and Resultsmentioning

confidence: 99%

Robust Motion Estimation Design Methodology

Heinrich

Bartels

Vleuten

et al. 2010

2010 Conference on Visual Media Production

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For motion-adaptive video retiming methods, the quest to lower the implementation complexity and improve the quality of motion estimation algorithms still continues. Comparing different motion estimators (MEs) and/or fine-tuning ME parameters is a time-consuming task, and it is even more demanding to identify the MEs with a robust performance among all the well-performing MEs. Therefore, a computer-aided design methodology is required to effectively explore the large design space. Such a methodology requires objective performance metrics. As it is hard to find perfect metrics, we present a design methodology that can use suboptimal measures and still identify robust MEs. The proposed methodology is demonstrated using two different MEs.

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Section: Discussion and Resultsmentioning

confidence: 99%

Robust Motion Estimation Design Methodology

Heinrich

Bartels

Vleuten

et al. 2010

2010 Conference on Visual Media Production

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“…7) is calculated for the x and y components separately. Similarly, the horizontal edge could be detected by calculating the absolute difference of motion vectors in block 3 X and 4 X .…”

Section: Occlusion Region Detectionmentioning

confidence: 99%

“…We expect an earlier proposal 3 , which aims at reducing the artifacts, to be sub-optimal, given the complexity of the heuristics involved. Therefore, in this paper, we aim to replace the heuristics with a methodology based on "trained filters".…”

Section: Introductionmentioning

confidence: 99%

Improved picture-rate conversion using classification-based LMS-filters

Heinrich

Cordes

et al. 2009

SPIE Proceedings

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Due to the recent explosion of multimedia formats and the need to convert between them, more attention is drawn to picture rate conversion. Moreover, growing demands on video motion portrayal without judder or blur requires improved format conversion. The simplest conversion repeats the latest picture until a more recent one becomes available. Advanced methods estimate the motion of moving objects to interpolate their correct position in additional images. Although motion blur and judder have been reduced using motion compensation, artifacts, especially around the moving objects in sequences with fast motion, may be disturbing. Previous work has reduced this so-called "halo" artifact, but the overall result is still perceived as sub-optimal due to the complexity of the heuristics involved. In this paper, we aim at reducing the heuristics by designing LMS up conversion filters optimized for pre-defined local spatio-temporal image classes. Design and evaluation, and a benchmark with earlier techniques will be discussed. In general, the proposed approach gives better results.

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“…More sophisticated algorithms use motion estimation (ME) and compensation [5] in order to improve the quality of the interpolated images. Despite the improvement on smooth motion portrayal, motion compensated interpolation (MCI) often introduces artifacts due to incorrect motion vectors or sub-optimal interpolation methods [1]. These are often visible at the fore-background transitions of moving objects, i.e.…”

Section: Introductionmentioning

confidence: 99%