Elements of information theory
Elements of information theory
3D Pose Estimation by Directly Matching Polyhedral Models to Gray Value Gradients
International Journal of Computer Vision
Model-Based Localisation and Recognition of Road Vehicles
International Journal of Computer Vision
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Mutual Information Based Evaluation of 3D Building Models
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Alignment by maximization of mutual information
Alignment by maximization of mutual information
Object detection using a cascade of 3d models
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Automatic registration of color images to 3D geometry
Proceedings of the 2009 Computer Graphics International Conference
PCA based regional mutual information for robust medical image registration
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
| Hi-index | 0.00 |
Mutual information has been used for matching and registering 3D models to 2D images. However, in Viola’s original framework [1], surface albedo variance is assumed to be minimal when measuring similarity between 3D models and 2D image data using mutual information. In reality, most objects have textured surfaces with different albedo values across their surfaces, and direct application of this method in such circumstances will fail. To solve this problem, we propose to include spatial information into the original formulation by using histogram-based features of local regions that are robust to local but significant albedo variation. Neighborhood Extended Gaussian Images (NEGI) are used as descriptors to represent local surface regions on the 3D model, while pixel intensity data are considered within corresponding region windows on the image. Experiments on aligning 3D car models in cluttered scenes using this new framework demonstrate substantial improvement as compared to the original pixel-wise mutual information approach.