A novel camera calibration method for fish-eye lenses using line features

In this paper, a novel method for the fish-eye lens calibration is presented. The method required only a 2D calibration plane containing straight lines i.e., checker board pattern without a priori knowing the poses of camera with respect to the calibration plane. The image of a line obtained from fish-eye lenses is a conic section. The proposed calibration method uses raw edges, which are pixels of the image line segments, in stead of using curves obtained from fitting conic to image edges. Using raw edges is more flexible and reliable than using conic section because the result from conic fitting can be unstable. The camera model used in this work is radially symmetric model i.e., bivariate non-linear function. However, this approach can use other single view point camera models. The geometric constraint used for calibrating the camera is based on the coincidence between point and line on calibration plane. The performance of the proposed calibration algorithm was assessed using simulated and real data

ROTATION MATRIX SAMPLING SCHEME FOR MULTIDIMENSIONAL PROBABILITY DISTRIBUTION TRANSFER

This paper address the problem of rotation matrix sampling used for multidimensional probability distribution transfer. The distribution transfer has many applications in remote sensing and image processing such as color adjustment for image mosaicing, image classification, and change detection. The sampling begins with generating a set of random orthogonal matrix samples by Householder transformation technique. The advantage of using the Householder transformation for generating the set of orthogonal matrices is the uniform distribution of the orthogonal matrix samples. The obtained orthogonal matrices are then converted to proper rotation matrices. The performance of using the proposed rotation matrix sampling scheme was tested against the uniform rotation angle sampling. The applications of the proposed method were also demonstrated using two applications i.e., image to image probability distribution transfer and data Gaussianization

3D Modeling from Multi-views Images for Cultural Heritage in Wat-Pho, Thailand

In Thailand, there are several types of (tangible) cultural heritages. This work focuses on 3D modeling of the heritage objects from multi-views images. The images are acquired by using a DSLR camera which costs around $1,500 (camera and lens). Comparing with a 3D laser scanner, the camera is cheaper and lighter than the 3D scanner. Hence, the camera is available for public users and convenient for accessing narrow areas. The acquired images consist of various sculptures and architectures in Wat-Pho which is a Buddhist temple located behind the Grand Palace (Bangkok, Thailand). Wat-Pho is known as temple of the reclining Buddha and the birthplace of traditional Thai massage. To compute the 3D models, a diagram is separated into following steps; Data acquisition, Image matching, Image calibration and orientation, Dense matching and Point cloud processing. For the initial work, small heritages less than 3 meters height are considered for the experimental results. A set of multi-views images of an interested object is used as input data for 3D modeling. In our experiments, 3D models are obtained from MICMAC (open source) software developed by IGN, France. The output of 3D models will be represented by using standard formats of 3D point clouds and triangulated surfaces such as .ply, .off, .obj, etc. To compute for the efficient 3D models, post-processing techniques are required for the final results e.g. noise reduction, surface simplification and reconstruction. The reconstructed 3D models can be provided for public access such as website, DVD, printed materials. The high accurate 3D models can also be used as reference data of the heritage objects that must be restored due to deterioration of a lifetime, natural disasters, etc

Satellite images combined with field data reveal negative changes in the distribution of babassu palms after clearing off amazonian forests

International audienceWhen the Amazonian rain forest is cut to create pasture, some of the original vegetal species survive clearing, even expressing their ability to invade agro-systems. It is true of the babassu palm, which can be considered, paradoxically, a natural resource by the "Interstate Movement of Babassu Fruit Breaker Women" or as native weed by land owners-farmers. To manage potential conflict of land uses, we study here the current density of this palm tree in different habitats, based on a combination of field data and remote sensing data. Firstly, we checked that the field survey methodology (i.e., counting free-trunk palm trees over 20 cm in circumference) provides density values compatible with those stemming from satellite images interpretation. We can see then that, a PA-Benfica Brazilian territory revealed an average density of the babassu lower in pastures (2.86 ind/ha) than in the dense forest (4.72 ind/ha) from which they originate and than in fallow land (4.31 ind/ ha). We analyze in detail density data repartition in three habitats and we discuss results from the literature on the density of this palm tree versus its resilience at different developmental stages after forest clearing, depending on anthropogenic -or not- factors, including solar radiation, fire, weeding, clear cutting, burying fruit, and competition with forage grass. All these results can be exploited for the design of future management plans for the babassu palm and we think that the linked methodology and interdisciplinary approach can be extended to others palms and trees species in similar problematic issues