Multi-modal stereo-vision using infrared / visible camera pairs

Download

index.pdf

Date

2014

Author

Yaman, Mustafa

Metadata

Show full item record

Item Usage Stats

153
views

169
downloads

In this thesis, a novel method for computing disparity maps from a multi-modal stereo-vision system composed of an infrared-visible camera pair is introduced. The method uses mutual information as the basic similarity measure where a segmentation based adaptive windowing mechanism is proposed along with a novel mutual information computation surface for greatly enhancing the results. Besides, the method incorporates joint prior probabilities when computing the cost matrix in addition to negative mutual information measures. A novel adaptive cost aggregation method is also proposed using computed cost confidences and resulting minimum cost disparities that are confident enough are fitted planes in segments. The segments are refined by iteratively splitting and merging according to the fitted confident disparities that helps to reduce the dependence of the disparity computation to the initial segmentation. Finally, all the steps are repeated iteratively where more accurate joint probabilities are calculated by sing previous iteration’s disparity map. Two multi-modal stereo image datasets are generated for evaluating the method and the state of the art methods confronted in literature; the synthetically altered image pairs from the Middlebury Stereo Evaluation Dataset, and our own dataset of Kinect Device infrared- visible camera image pairs, which can function as a benchmark for multi-modal stereo-vision methods. On these datasets, it is presented that (i) the proposed method improves the quality of existing MI formulation, (ii) the proposed method outperforms state of the art methods in literature, and (iii) the proposed method can provide depth comparable to the quality of Kinect depth data.

Subject Keywords

Stereoscopic cameras., Stereoscopic views., Imaging systems., Image processing.

URI

http://etd.lib.metu.edu.tr/upload/12618177/index.pdf
https://hdl.handle.net/11511/24192

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Utility based and user defined scoring based mining of sequential patterns Kırmemiş Alkan, Öznur; Karagöz, Pınar; Department of Computer Engineering (2015) In this thesis, a novel method for computing disparity maps from a multi-modal stereo-vision system composed of an infrared-visible camera pair is introduced. The method uses mutual information as the basic similarity measure where a segmentation based adaptive windowing mechanism is proposed along with a novel mutual information computation surface for greatly enhancing the results. Besides, the method incorporates joint prior probabilities when computing the cost matrix in addition to negative mutual info...
Multimodal Stereo Vision Using Mutual Information with Adaptive Windowing Yaman, Mustafa; Kalkan, Sinan (2013-05-23) This paper proposes a method for computing disparity maps from a multimodal stereovision system composed of an infrared and a visible camera pair. The method uses mutual information (MI) as the basic similarity measure where a segmentation-based adaptive windowing mechanism is proposed for greatly enhancing the results. On several datasets, we show that (i) our proposal improves the quality of existing MI formulation, and (ii) our method can provide depth comparable to the quality of Kinect depth data.
Multi-baseline stereo correction for silhouette-based 3D model reconstruction from multiple images Mulayim, AY; Atalay, Mehmet Volkan (2001-01-25) Silhouette based reconstruction algorithm is simple and robust for 3D volume estimation of an object. However? it has two main drawbacks: insufficient number of viewing positions and the inability to detect concavity regions. Starting from an initial convex hull of the object to be modeled which is generated by a silhouette based reconstruction, an algorithm based on photoconsistency is described. The algorithm basically carves the excess volume elements using the multi-baseline stereo information. Result o...
Multi-image region growing for integrating disparity maps Leloglu, UĞUR MURAT; Halıcı, Uğur (1999-01-01) In this paper, a multi-image region growing algorithm to obtain planar 3-D surfaces in the object space from multiple dense disparity maps, is presented. A surface patch is represented by a plane equation and a set of pixels in multiple images. The union of back projections of all pixels in the set onto the infinite plane, forms the surface patch. Thanks to that hybrid representation of planar surfaces, region growing (both region aggregation and region merging) is performed on all images simultaneously. Pl...
An iterative adaptive multi-modal stereo-vision method using mutual information Yaman, Mustafa; Kalkan, Sinan (2015-01-01) We propose a method for computing disparity maps from a multi-modal stereo-vision system composed of an infrared-visible camera pair. The method uses mutual information (MI) as the basic similarity measure where a segment-based adaptive windowing mechanism is proposed along with a novel MI computation surface with joint prior probabilities incorporated. The computed cost confidences are aggregated using a novel adaptive cost aggregation method, and the resultant minimum cost disparities in segments are plan...

Citation Formats

M. Yaman, “Multi-modal stereo-vision using infrared / visible camera pairs,” Ph.D. - Doctoral Program, Middle East Technical University, 2014.