Cache-efficient graph cuts on structured grids

Jamriška, Ondřej; Sýkora, Daniel; Hornung, Alexander

doi:10.1109/cvpr.2012.6248113

Cited by 39 publications

(37 citation statements)

References 34 publications

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“…The GPU based optical flow [25,26] method is used to extract vehicle flows in a road surveillance video. We also applied the graph cut library [24] to compute the surface that can seamlessly transit one video to another. Finally, we apply the conjugate gradient method to solve the Poisson blending problem.…”

Section: Resultsmentioning

confidence: 99%

Traffic situation visualization based on video composition

Hsieh

Wang

2016

Computers & Graphics

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a b s t r a c tVehicle detectors (VDs) are usually distributed in a road network to detect macroscopic traffic situations. These detectors provide global information such as vehicle flows, average speed, and road occupancy. Given that the collected statistic data are difficult for citizens to interpret, we visualize the data by providing users with realistic traffic videos. To achieve this aim, our system collects the surveillance videos and VD data that represent the traffic situation of a position. It then builds the connection between these two types of data. Considering the distribution of VDs is much denser than that of surveillance cameras, for those road segments with a VD but without a surveillance camera, one can utilize our system to synthesize videos for visually depicting the traffic situations over there. That is, we estimate vehicle flows from a video and apply the regression model to build the mapping between the flows and VD data. After that, given by a VD dataset, our system retrieves videos that match the VD data and seamlessly composes them to synthesize a traffic video. The evaluations and the experimental results demonstrate the feasibility of our system.

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Section: Resultsmentioning

confidence: 99%

Traffic situation visualization based on video composition

Hsieh

Wang

2016

Computers & Graphics

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“…Segmentation was performed on a Pentium Dual-Core 2.93 GHz processor with 2GB RAM and used the graph-cut software provided by [12]. All images are gray-scale.…”

Section: Resultsmentioning

confidence: 99%

Iterative graph cuts segmentation with local constraints

Dong

Yan

Chen

et al. 2013

2013 Ninth International Conference on Natural Computation (ICNC)

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Most existing stroke-based graph cut image segmentation techniques use only intensity information of strokes to update intensity distributions of object and background. Accordingly, fluctuation effect may occur unexpectedly as a result of the global effect of regional term in the graph cut framework. In this note we present an iterative graph cuts-based image segmentation technique which incorporates local constraints. A new energy function with local constraints term generated following additional seed points is formulated and is minimized to obtain a globally optimal segmentation. We tested the method on cone-beam CT data of printed circuit board and comparatively found the strength of the proposed method in accuracy and controllability.

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“…Our future work will focus on improving the efficiency with graphics processor units (GPUs). 35 We will combine the proposed method with machine learning methods and make the model an automatic one.…”

Section: Discussionmentioning

confidence: 99%

3D liver segmentation using multiple region appearances and graph cuts

Peng

et al. 2015

Medical Physics

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Purpose: Efficient and accurate 3D liver segmentations from contrast-enhanced computed tomography (CT) images play an important role in therapeutic strategies for hepatic diseases. However, inhomogeneous appearances, ambiguous boundaries, and large variance in shape often make it a challenging task. The existence of liver abnormalities poses further difficulty. Despite the significant intensity difference, liver tumors should be segmented as part of the liver. This study aims to address these challenges, especially when the target livers contain subregions with distinct appearances. Methods: The authors propose a novel multiregion-appearance based approach with graph cuts to delineate the liver surface. For livers with multiple subregions, a geodesic distance based appearance selection scheme is introduced to utilize proper appearance constraint for each subregion. A special case of the proposed method, which uses only one appearance constraint to segment the liver, is also presented. The segmentation process is modeled with energy functions incorporating both boundary and region information. Rather than a simple fixed combination, an adaptive balancing weight is introduced and learned from training sets. The proposed method only calls initialization inside the liver surface. No additional constraints from user interaction are utilized. Results: The proposed method was validated on 50 3D CT images from three datasets, i.e., Medical Image Computing and Computer Assisted Intervention (MICCAI) training and testing set, and local dataset. On MICCAI testing set, the proposed method achieved a total score of 83.4 ± 3.1, outperforming nonexpert manual segmentation (average score of 75.0). When applying their method to MICCAI training set and local dataset, it yielded a mean Dice similarity coefficient (DSC) of 97.7% ± 0.5% and 97.5% ± 0.4%, respectively. These results demonstrated the accuracy of the method when applied to different computed tomography (CT) datasets. In addition, user operator variability experiments showed its good reproducibility. Conclusions: A multiregion-appearance based method is proposed and evaluated to segment liver. This approach does not require prior model construction and so eliminates the burdens associated with model construction and matching. The proposed method provides comparable results with state-of-the-art methods. Validation results suggest that it may be suitable for the clinical use. C 2015 American Association of Physicists in Medicine. [http://dx

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Cache-efficient graph cuts on structured grids

Cited by 39 publications

References 34 publications

Traffic situation visualization based on video composition

Traffic situation visualization based on video composition

Iterative graph cuts segmentation with local constraints

3D liver segmentation using multiple region appearances and graph cuts

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