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Active contours or snakes are widely used for segmentation and tracking. We propose a new active contour model, which converges reliably even when the initialization is far from the object of interest. The proposed segmentation technique uses an external energy function where the energy slowly decreases in the vicinity of an edge. This new energy function is calculated using an efficient dual scan...
The raster-vector conversion of remote sensing image is a very important task in the extraction and updating of linear objects in cartographic processes. In this paper we present a vectorization method, based on constrained Delaunay triangulation, for line extraction. The constraints are provided by a preprocessing step insuring that these edges belong to line structures in the original image. The...
A multi-modal biometric system based on palm dorsal vein and hand shape is proposed in this paper. Palm dorsal vein images are captured with an infra-red sensitive camera under near infra-red illumination. Gaussian matched filter is performed to extract vein patterns from Regions Of Interest (ROI) cropped from original images. As for hand shape features, width, height and triangle features are extracted...
Vessel enhancement and segmentation aim at (binary) per-pixel segmentation considering certain local features as probabilistic vessel indicators. We propose a new methodology to combine any local probability map with local directional vessel information. The resulting global vessel segmentation is represented as a set of discrete streamlines populating the vascular structures and providing additional...
Neighborhood coding was proposed to encode binary images. Previously, this coding scheme presented good results in the problem of handwritten character recognition. In this article, we extended this coding scheme so that it can be applied as an image shape descriptor and in a bilevel image compression method. An algorithm to reduce the number of codes needed to reconstruct the image without loss of...
We propose to evaluate our sparsity driven people localization framework on crowded complex scenes. The problem is recast as a linear inverse problem. It relies on deducing an occupancy vector, i.e. the discretized occupancy of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector,...
Unsupervised over-segmentation of an image into super-pixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feature vectors and as a starting point for the final segmentation. In this paper we investigate incorporating a priori information into superpixel segmentations. We learn a probabilistic model that describes the spatial density...
A novel parametric deformable model of a goal object controlled by shape and appearance priors learned from co-aligned training images is introduced. The shape prior is built in a linear space of vectors of distances to the training boundaries from their common centroid. The appearance prior is modeled with a spatially homogeneous 2nd-order Markov-Gibbs random field (MGRF) of gray levels within each...
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models or temporal models for dynamics are not required or used. Tracking facial features simply becomes the independent tracking of a set of points on the face. This allows us to cope with facial configurations not present in the...
We propose that appearance descriptors derived from the complete animacy of an object during its scene presence more comprehensively capture the essence of an object than descriptors that merely encode uncorrelated sets of its instantaneous appearances. During its frame presence, an object presents itself in many poses with differing frequencies, thus generating multiple modes of varying strengths...
Based on the study of patterns used in many fast algorithms for the block-matching motion estimation (BMME), a new search pattern, LP (line search pattern), was introduced in this paper. LP is also a simplified square search pattern as TP(Triangle search Pattern). By combing LP with DP(diamond search pattern), a fast BMA (BMME Algorithm), DLS (diamond-line search), was also proposed in this paper...
This paper proposes a learnt data-driven approach to the accurate, real-time tracking of lip shapes using only intensity information i.e. grey-scale images. This has the advantage that constraints such as a-priori shape models or temporal models for dynamics are not required or used. Tracking the lip shape is simply the independent tracking of a set of points that lie on the lip's contour. This allows...
We perform shape matching by transforming the problem of establishing shape correspondences into an image registration problem. At each vertex on the shape, we calculate a shape feature and encode this feature as image intensity at appropriate positions in the image domain. Calculating multiple features at each vertex and encoding them into the image domain results in a vector-valued feature image...
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