A Modified Census Transform Based on the Neighborhood Information for Stereo Matching Algorithm

Ma, Long; Li, Jingjiao; Ma, Ji; Zhang, Hanyue

doi:10.1109/icig.2013.113

Cited by 33 publications

(24 citation statements)

References 7 publications

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“…The non-parametric Census transform [2] is applied on im l and im r , with a sparse modified approach from [12]. It converts each pixel inside a moving window into a string of bits C(i, j) (see Eq.…”

Section: Methods 2 1 Matching Cost Computationmentioning

confidence: 99%

“…6 Example of the region of interest for heart1 and heart2 models. The points marked with magenta color were not included in the evaluation of the methods Census transform and the Aggregation cost of Method 2 are taken from [12], where the authors identify the optimal parameters taking into consideration accuracy and computational time. …”

Section: Quantitative Evaluationmentioning

confidence: 99%

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Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

et al. 2015

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Purpose: Single Incision Laparoscopic Surgery (SILS) decreases post-operative infections, but introduces limitations in the surgeon's manoeuverability and in the surgical field of view. This work aims at enhancing intraoperative surgical visualization by exploiting the 3D information about the surgical site. An interactive guidance system is proposed wherein the pose of pre-operative tissue models is updated online. A critical process involves the intraoperative acquisition of tissue surfaces. It can be achieved using stereoscopic imaging and 3D reconstruction techniques. This work contributes to this process by proposing new methods for improved dense 3D reconstruction of soft tissues, which allows a more accurate deformation identification and facilitates the registration process.Methods: Two methods for soft tissue 3D reconstruction are proposed: Method 1 follows the traditional approach of the block matching algorithm. Method 2 performs a non-parametric Modified Census Transform to be more robust to illumination variation. The Simple Linear Iterative Clustering (SLIC) super pixel al- gorithm is exploited for disparity refinement by filling holes in the disparity images.Results: The methods were validated using two video datasets from the Hamlyn Centre, achieving an accuracy of 2.95 mm and 1.66 mm respectively. A comparison with ground truth data demonstrated the disparity refinement procedure: (i) increases the number of reconstructed points by up to 43%; (ii) does not a↵ect the accuracy of the 3D reconstructions significantly.Conclusion: Both methods give results that compare favourably with the state-of-the-art methods. The computational time constraints their applicability in realtime, but can be greatly improved by using a GPU implementation.

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Section: Methods 2 1 Matching Cost Computationmentioning

confidence: 99%

Section: Quantitative Evaluationmentioning

confidence: 99%

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Therefore, a smaller threshold should be selected. By analyzing the adjacent points of multiple images and simulating the Census changes under different thresholds, we get that the suitable interval of thresholds is [15][16][17][18][19][20][21][22][23][24]. The threshold of this algorithm is 20.…”

Section: Improved Census Transformmentioning

confidence: 99%

Design and implementation of wireless multimedia sensor network node based on FPGA and binocular vision

Shang

Wang

Sun

2018

J Wireless Com Network

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According to the actual demand of the wireless sensor network for multimedia information acquisition, the new multimedia wireless sensor node is designed and implemented with FPGA as the core and Zigbee wireless communication. On the multimedia nodes, sensors such as binocular camera and accelerometer are configured to realize real-time perception and acquisition of environmental information and image data, and the short distance wireless communication and detection ability is formed through Zigbee protocol. When the test distance is not more than 60 m, the measured data fluctuate around the theoretical curve, and the communication is reliable. When the distance of the node is within the 14 m, the data transmission has no error. In view of the fact that the mismatch rate of the traditional Census transform is high under the condition of accuracy and noise, an improved Census transform stereo matching algorithm is proposed, which is applied to the nodes of multimedia sensor network. The experimental results show that this scheme can realize the data transmission and processing of wireless sensor network nodes and has strong operation capability and visual matching precision while reducing power consumption.

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“…From their results, the feature-based matching accuracy was low because this approach only targeted the object features and less sensitive to occlusion and textureless areas. Another approaches for pixel-based matching technique were shown by the works of Samadi and Othman (2013), Jung et al (2014) and Ma et al (2013a). Samadi and Othman (2013) stated that the census based pixel matching was implemented with the reduction of bits on the comparison numbers.…”

Section: Related Work On Stereo Matching Algorithmsmentioning

confidence: 99%

“…Their work produce a better quality disparity map. Ma et al (2013a) implemented census transform based on neighbourhood information. They have utilised more bits to represent the difference between the pixel and its neighbour.…”

Section: Related Work On Stereo Matching Algorithmsmentioning

confidence: 99%

Stereo Matching Algorithm Based on Illumination Control to Improve the Accuracy

2016

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This paper presents a new method of pixel based stereo matching algorithm using illumination control. The state of the art algorithm for absolute difference (AD) works fast, but only precise at low texture areas. Besides, it is sensitive to radiometric distortions (i.e., contrast or brightness) and discontinuity areas. To overcome the problem, this paper proposes an algorithm that utilizes an illumination control to enhance the image quality of absolute difference (AD) matching. Thus, pixel intensities at this step are more consistent, especially at the object boundaries. Then, the gradient difference value is added to empower the reduction of the radiometric errors. The gradient characteristics are known for its robustness with regard to the radiometric errors. The experimental results demonstrate that the proposed algorithm performs much better when using a standard benchmarking dataset from the Middlebury Stereo Vision dataset. The main contribution of this work is a reduction of discontinuity errors that leads to a significant enhancement on matching quality and accuracy of disparity maps.

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A Modified Census Transform Based on the Neighborhood Information for Stereo Matching Algorithm

Cited by 33 publications

References 7 publications

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

Design and implementation of wireless multimedia sensor network node based on FPGA and binocular vision

Stereo Matching Algorithm Based on Illumination Control to Improve the Accuracy

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