Multimodal Stereo Vision Using Mutual Information with Adaptive Windowing

2013-05-23
Yaman, Mustafa
Kalkan, Sinan
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.

Suggestions

Multi-modal stereo-vision using infrared / visible camera pairs
Yaman, Mustafa; Kalkan, Sinan; Department of Computer Engineering (2014)
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...
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...
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...
Sensor Fusion of a Camera and 2D LIDAR for Lane Detection
Schmidt, Klaus Verner (null; 2019-04-26)
This paper presents a novel lane detection algorithm based on fusion of camera and 2D LIDAR data. On the one hand, objects on the road are detected via 2D LIDAR. On the other hand, binary bird’s eye view (BEV) images are acquired from the camera data and the locations of objects detected by LIDAR are estimated on the BEV image. In order to remove the noise generated by objects on the BEV, a modified BEV image is obtained, where pixels occluded by the detected objects are turned into background pixels. Then,...
Electromagnetic Object Recognition for Dielectric Coated Conductors Based on WD-PCA Type Fused Feature Extraction
Sayan, Gönül (2012-01-01)
This paper presents the application of a real-time electromagnetic object classification technique to recognize dielectric coated conducting objects using their wideband scattered signals received at arbitrary combinations of aspect and polarization. The suggested classifier design technique depends on the use of Singularity Expansion Method (SEM) to represent a given electromagnetic scatterer by its natural resonances. A quadratic time-frequency transformation, the Wigner distribution (WD), is used to extr...
Citation Formats
M. Yaman and S. Kalkan, “Multimodal Stereo Vision Using Mutual Information with Adaptive Windowing,” Kyoto, Japonya, 2013, vol. 1, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73993.