A Measure for Accuracy Disparity Maps Evaluation

Cabezas, Ivan; Padilla, Victor; Trujillo, María

doi:10.1007/978-3-642-25085-9_26

Cited by 16 publications

(7 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here we are restricting our discussion to binocular vision (left and right views). As discussed in [7] differences between two images, give depth information and these differences are known as disparities. In other words shift between stereocorresponding points is termed as disparity.…”

Section: Literature Surveymentioning

confidence: 99%

Depth perception in single rgb camera system using lens aperture and object size: a geometrical approach for depth estimation

Alphonse

Sriharsha

2021

SN Appl. Sci.

View full text Add to dashboard Cite

In recent years, with increase in concern about public safety and security, human movements or action sequences are highly valued when dealing with suspicious and criminal activities. In order to estimate the position and orientation related to human movements, depth information is needed. This is obtained by fusing data obtained from multiple cameras at different viewpoints. In practice, whenever occlusion occurs in a surveillance environment, there may be a pixel-to-pixel correspondence between two images captured from two cameras and, as a result, depth information may not be accurate. Moreover use of more than one camera exclusively adds burden to the surveillance infrastructure. In this study, we present a mathematical model for acquiring object depth information using single camera by capturing the in focused portion of an object from a single image. When camera is in-focus, with the reference to camera lens center, for a fixed focal length for each aperture setting, the object distance is varied. For each aperture reading, for the corresponding distance, the object distance (or depth) is estimated by relating the three parameters namely lens aperture radius, object distance and object size in image plane. The results show that the distance computed from the relationship approximates actual with a standard error estimate of 2.39 to 2.54, when tested on Nikon and Cannon versions with an accuracy of 98.1% at 95% confidence level.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Depth perception in single rgb camera system using lens aperture and object size: a geometrical approach for depth estimation

Alphonse

Sriharsha

2021

SN Appl. Sci.

View full text Add to dashboard Cite

show abstract

“…where z C (x) is the distance from point x C to the plane (O C , x C , y C ), containing the focal point O C , and f is the focal length. Cabezas et al [4] identified two elements that lack in the definition of metric (9). The first is that it does not take into account the a priori error made on the depth z C during the 3D reconstruction.…”

Section: Existing Assessment Metricsmentioning

confidence: 99%

Comparison of Optical Flow Methods under Stereomatching with Short Baselines

Dagobert¹,

Monzón²,

Sánchez³

2019

Image Processing on Line

View full text Add to dashboard Cite

This article studies the effectiveness of optical flow methods applied to short baseline image pairs under different noise levels. New metrics have been developed to analyze the results because the usual metrics are inadequate in a subpixel context. We have used the implementation of some standard optical flow methods adapted to the stereo problem. Our experiments show that the Brox et al. method produces the least errors, with a 60% success rate and a relative precision at 1/100th of a pixel. On the other hand, our comparison shows that a discontinuity preserving method, derived from Brox et al., also provides competitive results at the same time that it yields disparities with more details and correct contours. Source Code Source codes of Lucas-Kanade 1D, Robust Optical Flow 1D and Robust Discontinuity Preserving 1D algorithms are provided in the web page of the article 1 .

show abstract

“…The percentage of Bad Matched Pixels (BMP) measures the quantity of disparity estimation errors exceeding a threshold δ (equals to 1 pixel) [12]. The Sigma-Z-Error (SZE) measures the impact of estimation errors on a 3D reconstruction based on the distance between the real depth and the estimated depth, based on ground-truth disparity and estimated disparity, respectively [17]. The Mean Relative Error (MRE) is based on the ratio between the absolute difference of estimated disparity against ground-truth disparity, and ground-truth disparity [18].…”

Section: Experimental Validationmentioning

confidence: 99%

A Method for Reducing the Cardinality of the Pareto Front

Cabezas

Trujillo

2012

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Self Cite

View full text Add to dashboard Cite

Multi-objective problems are characterised by the presence of a set of optimal trade-off solutions-a Pareto front-, from which a solution has to be selected by a decision maker. However, selecting a solution from a Pareto front depends on large quantities of solutions to select from and dimensional complexity due to many involved objectives, among others. Commonly, the selection of a solution is based on preferences specified by a decision maker. Nevertheless a decision maker may have not preferences at all. Thus, an informed decision making process has to be done, which is difficult to achieve. In this paper, selecting a solution from a Pareto front is addressed as a multiobjective problem using two utility functions and operating in the objective space. A quantitative comparison of stereo correspondence algorithms performance is used as an application domain.

show abstract

A Measure for Accuracy Disparity Maps Evaluation

Cited by 16 publications

References 18 publications

Depth perception in single rgb camera system using lens aperture and object size: a geometrical approach for depth estimation

Depth perception in single rgb camera system using lens aperture and object size: a geometrical approach for depth estimation

Comparison of Optical Flow Methods under Stereomatching with Short Baselines

A Method for Reducing the Cardinality of the Pareto Front

Contact Info

Product

Resources

About