Ellipse-based camera calibration

An important task in most 3D vision systems is camera modeling . We present a calibration method designed for a good accuracy in the parameters estimation . Accurate image measurments are required to perform the camera model estimation. We suggest a technique, based upon surface photometry analysis, to compute robustly and accurately the moments of a shape in an image, and use them as inputs for the estimation algorithm. As a consequences, an ellipse-based camera calibration is introduced, which uses the relationships between the specification of a 3D-ellipse, the moments of its image and the calibration parameters . These equations are partially extended to models including distortions .En vision par ordinateur, il est souvent utile de connaître un modèle de la caméra pour pouvoir obtenir des informations 3D à partir des images. Nous présentons une méthode de calibration (ou calibrage) de caméra conçue pour fournir une estimation précise des paramètres du modèle de prise de vue. Pour avoir une bonne estimation, il est nécessaire avant tout d'avoir de bonnes mesures dans l'image. Nous avons choisi d'utiliser les moments géométriques d'une région comme les données 'image' à fournir à l'algorithme, car ils peuvent être calculés avec précision et robustesse en se fondant sur la photométrie des surfaces. Cela nous a conduits à développer une calibration à base d'ellipses. Pour cela, le lien exact entre la description d'une ellipse de l'espace 3D et les moments d'ordre inférieur ou égal à deux de sa projection a dû être explicité en fonction des paramètres de la calibration. Ces relations sont en partie étendues au cas où les distorsions sont modélisées

Region-Based Top-Down Segmentation Adapted to Stereo Matching

We present region based image processing algorithms participating in task sequencing for stereo vision. The algorithms described here are prior to stereo matching. Requirements in image similarity provide helpful additional knowledge for their improvement. We describe first a resursive region division algorithm using a thresholding method based on contrast maximization. The regions are processed in parallel and absorb their noise before being thresholded. Subsequent morphological processes improve similarity and matching results. Additional knowledge is produced by analytical processes, and is useful for both segmentation and match control. Results are presented for a stereo pair of gray level images, see figure 1. 1 Introduction The main tasks contributing to 3-D reconstruction of a scene are : segmentation of a stereo pair of images, stereo matching and depth computation. The success of each job depends on the results of the previous one. The basic tenet of our study is that, althou..

Interactive Animation of Object Orientations

International audienc

Integration of Synthetic Surface Relief in Range Images

NRC publication: Ye

Statistical approach to boar semen head classification based on intracellular intensity distribution

We propose a technique to compute the fraction of boar spermatozoid heads which present an intracellular density distribution pattern hypothesized as normal by veterinary experts. This approach offers a potential for digital image processing estimation of sperm capacitation which can substitute expensive staining techniques. We extract a model distribution from a training set of heads assumed as normal by veterinary experts. We also consider two other training sets, one with heads similar to the normal pattern and another formed by heads that substantially deviate from that pattern. For each spermatozoid head, a deviation from the model distribution is computed. This produces a conditional probability distribution of that deviation for each set. Using a set of test images, we determine the fraction of normal heads in each image and compare it with the result of expert classification. This yields an absolute error below 0.25 in the 89% of the samples