Catálogo de publicaciones - libros

A new method for unsupervised clustering of shapes is here proposed. This method is based on two steps: in the first step a preliminary clusterization is obtained by considering the distance among shapes after alignment with procrustes analysis [1],[2]. This step is based on the minimization of the functional ()=+(1/)() where is the total number of clusters, () is the intra-cluster variability and is an appropriate constant. In the second step, the curvature of shapes belonging to clusters obtained in the first step is examined to i) identify possible outliers and to ii) introduce a further refinement of clusters. The proposed method was tested on the Kimia, Surrey and MPEG7 shape databases and was able to obtain correct clusters, corresponding to perceptually homogeneous object categories. The proposed method was able to distinguish shapes with subtle differences, such as birds with one or two feet and to distinguish among very similar animal species....

In this paper a new approach is presented for markerless pose tracking in augmented reality. Using a tracking by detection approach, we estimate the 3D camera pose by detecting natural feature points in each input frame and building correspondences between 2D feature points. Instead of modeling the 3D environment, which is changing constantly and dynamically, we use a virtual square to define a 3D reference coordinate system. Camera pose can hence be estimated relative to it and the calculated 3D pose parameters can be used to render virtual objects into the real world. We propose and implement several strategies for robust matching, pose estimation and refinement. Experimental evaluation has shown that the approach is capable of online pose tracking and augmentation.

In this paper we propose a lip detector based on adaptive thresholding for hue-transformed face images. The adaptation is performed according to the confidence values of the estimated lip regions. The confidence of lip means how much similarity exists between the detected lip region and a true lip. We construct simple fuzzy rules of the confidence using true lip statistics of center position, width and height. The threshold value is adaptively changed so that the confidence of a renewed lip region is maximized. By lip detection experiments with VidTimit database we demonstrate the performance enhancement of our proposed method.

In this work we present an iterative multi-scale algorithm for motion estimation that follows mechanisms of motion processing in the human brain. Keeping the properties of a previously presented neural model of cortical motion integration we created a computationally fast algorithmic implementation of the model. The novel contribution is the extension of the algorithm to operate on multiple scales without the disadvantages of typical coarse-to-fine approaches. Compared to the implementation with one scale our multi-scale approach generates faster dense flow fields and reduces wrong motion estimations. In contrast to other approaches, motion estimation on the fine scale is biased by the coarser scales without being corrupted if erroneous motion cues are generated on coarser scales, e.g., when small objects are overlooked. This multi-scale approach is also consistent with biological observations: The function of fast feedforward projections to higher cortical areas with large receptive fields and feedback connections to earlier areas as suggested by our approach might contribute to human motion estimation.

In this paper, we study the application of the box counting method (BCM) to estimate the fractal dimension of 3D plant foliage. We use artificial crowns with known theoretical fractal dimension to characterize the accuracy of the BCM and we extend the approach to 3D digitized plants. In particular, errors are experimentally characterized for the estimated values of the fractal dimension. Results show that, with careful protocols, the estimated values are quite accurate. Several limits of the BCM are also analyzed in this context. This analysis is used to introduce a new estimator, derived from the BCM estimator, whose behavior is characterized.

The purpose of our project is to develop an image guided system for the medialization laryngoplasty. One of the fundamental challenges in our system is to accurately register the preoperative 3D CT data to the intraoperative 3D surfaces of the patient. In this paper, we will present a combined surface and fiducial based registration method to register the preoperative 3D CT data to the intraoperative surface of larynx. To accurately model the exposed surface area, an active illumination based stereo vision technique is used for the surface reconstruction. To register the point clouds from the intraoperative stage to the preoperative 3D CT data, a shape priori based ICP method is proposed to quickly register the two surfaces. The proposed approach is capable of tracking the fiducial markers and reconstructing the surface of larynx with no damage to the anatomical structure. Although, the proposed method is specifically designed for the image guided laryngoplasty, it can be applied to other image guided surgical areas. We used off-the-shelf digital cameras, LCD projector and rapid 3D prototyper to develop our experimental system. The final RMS error in the registration is less than 1mm.

This paper proposes a survey of vision-based human computer interfaces for several key-fields in health care: data visualization for image-guided diagnosis, image-guided therapy planning and surgery, the operating room, assistance to motor-impaired patients, and monitoring and support of elderly. The emphasis is on the contribution of the underlying computer vision techniques to the usability and usefullness of interfaces for each specific domain.

In this paper, we propose a maximum a posteriori formulation to the multiple target tracking problem. We adopt a graph representation for storing the detected regions as well as their association over time. The multiple target tracking problem is formulated as a multiple paths search in the graph. Due to the noisy foreground segmentation, an object may be represented by several foreground regions and one foreground region may corresponds to multiple objects. We introduce merge, split and mean shift operations that add new hypothesis to the measurement graph in order to be able to aggregate, split detected blobs or re-acquire objects that have not been detected during stop-and-go-motion. To make full use of the visual observations, we consider both motion and appearance likelihood. Experiments have been conducted on both indoor and outdoor data sets, and a comparison has been carried to assess the contribution of the new tracker.

Reproducing realistic facial expressions is an important challenge in human computer interaction. In this paper we propose a novel method of modeling and recovering the transitions between different expressions through the use of an autoregressive process. In order to account for computational complexity, we adopt a compact face representation inspired from MPEG-4 standards while in terms of expressions a well known Facial Action Unit System (FACS) comprising the six dominant ones is considered. Then, transitions between expressions are modeled through a time series according to a linear model. Explicit constraints driven from face anthropometry and points interaction are inherited in this model and minimize the risk of producing non-realistic configurations. Towards optimal animation performance, a particular hardware architecture is used to provide the 3D depth information of the corresponding facial elements during the learning stage and the Random Sampling Consensus algorithm for the robust estimation of the model parameters. Promising experimental results demonstrate the potential of such an approach.

Reproducing high quality facial expressions is an important challenge in human-computer interaction. Laser-scanners offer an expensive solution to such a problem with image based alternatives being a low-resolution alternative. In this paper, we propose a new method for stereo reconstruction from multiple video pairs that is capable of producing high resolution facial models. To this end, a combinatorial optimization approach is considered and is coupled in time to produce high resolution depth maps. Such optimization is addressed with the use of graph-cuts leading to precise reconstruction of facial expressions that can then be used for animation.