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This work presents a robust normalization technique by cascading a speech enhancement method followed by a feature vector normalization algorithm. To provide speech enhancement the Spectral Subtraction (SS) algorithm is used; this method reduces the effect of additive noise by performing a subtraction of the noise spectrum estimate over the complete speech spectrum. On the other hand, an empirical...
An essential functionality for advanced driver assistance systems (ADAS) is road segmentation, which directly supports ADAS applications like road departure warning and is an invaluable background segmentation stage for other functionalities as vehicle detection. Unfortunately, road segmentation is far from being trivial since the road is in an outdoor scenario imaged from a mobile platform. For instance,...
Recent stereo cameras provide reliable 3D reconstructions. These are useful for selecting ground-plane points, register them and building mosaics of cluttered ground planes. In this paper we propose a 2D Iterated Closest Point (ICP) registration method, based on the distance transform, combined with a fine-tuning-registration step using directly the image data. Experiments with real data show that...
Lines are particularly important features for different tasks such as calibration, structure from motion, 3D reconstruction in computer vision. However, line detection in catadioptric images is not trivial because the projection of a 3D line is a conic eventually degenerated. If the sensor is calibrated, it has been already demonstrated that each conic can be described by two parameters. In this way,...
This work presents a content-based image retrieval system of general purpose that deals with cluttered scenes containing a given query object. The system is flexible enough to handle with a single image of an object despite its rotation, translation and scale variations. The image content is divided in parts that are described with a combination of features based on geometrical and color properties...
The recognition of emotional information is a key step toward giving computers the ability to interact more naturally and intelligently with people. This paper presents a completely automated real-time system for facial expression’s recognition based on facial features’ tracking and a simple emotional classification method. Facial features’ tracking uses a standard webcam and requires no specific...
The automatic transcription of broadcast news and meetings involves the segmentation, identification and tracking of speaker turns during each session, which is known as speaker diarization. This paper presents a simple but effective approach to a slightly different task, called speaker tracking, also involving audio segmentation and speaker identification, but with a subset of known speakers, which...
This paper introduces a technique for region-based pose tracking without the need to explicitly compute contours. We assume a surface model of a rigid object and at least one calibrated camera view. The goal is to find the pose parameters that optimally fit the model surface to the contour of the object seen in the image. In contrast to conventional contour-based techniques, which acquire the contour...
Active Contours are a widely used Pattern Recognition technique. Classical Active Contours are curves evolutionate by minimizing an energy function. However, they can detect only one o bject within an image with several objects, and the solution is highly dependent on parameters in its formulation. A solution can be found in Geodesic Active Contours (GAC). We have developed a version of this technique...
There is strong need for research in transcoding technologies to enable smooth displacement from MPEG-2 to H.264/AVC since H.264/AVC has been standardized as international standard. In this paper, a novel rate control algorithm for MPEG-2 to H.264/AVC transcoding, which adopting a new block activity measurement, is proposed. Specifically, the standard deviation of the residual error is introduced...
We address the problem of estimating 3-D motion from acoustic images acquired by high-frequency 2-D imaging sonars deployed in underwater. Utilizing a planar approximation to scene surfaces, two-view homography is the basis of a nonlinear optimization method for estimating the motion parameters. There is no scale factor ambiguity, unlike the case of monocular motion vision for optical images. Experiments...
We present a new geometry compression algorithm for manifold 3D meshes based on octree coding. For a given mesh, regular volume grids are built with an adaptive octree. For each grid point, a binary sign, which indicates inside or outside of the mesh, is generated based on the distance to the mesh. In each leaf cell having a vertex, a least square fitting plane is created for a localized geometry...
This paper introduces a general methodology for detecting and reducing the errors in a handwriting recognition task. The methodology is based on confidence modeling and its main difference is the use of two parallel classifiers for error assessment. The experimental benchmark associated with this approach is described as well as exhaustive results are provided for two real world recognizers on a large...
In recent years, 6 Degrees Of Freedom (DOF) Pose Estimation and 3D Mapping is becoming more important not only in the robotics community for applications such as robot navigation but also in computer vision for the registration of large surfaces such as buildings and statues. In both situations, the robot/camera position and orientation must be estimated in order to be used for further alignment of...
The challenge of interest point detectors is to find, in an unsupervised way, keypoints easy to extract and at the same time robust to image transformations. In this paper, we present a novel set of saliency features that takes into account the region inhomogeneity in terms of intensity and shape. The region complexity is estimated at real-time by means of the entropy of the grey-level information...
Piecewise-linear methods accomplish the registration by dividing the images in corresponding triangular patches, which are individually mapped through affine transformations. For this process to be successful, every pair of corresponding patches must lie on projections of a 3D plane surface; otherwise, the registration may generate undesirable artifacts, such as broken lines, which diminish the registration...
We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information...
This paper proposes a new method for simplifying a 2d shape boundary based on its phase congruence and the optimisation of a function criterion. The phase congruence is a dimensionless feature that stands out boundary salient structures over different scales allowing a hierarchical fast optimisation process over the detected structures. The proposed method has been compared with other two well-known...
In this paper we propose a Bayesian filter for the Kadir Scale Saliency Detector. Such filter is addressed to deal with the main bottleneck of the Kadir detector, which is the scale space search for all pixels in the image. Given some statistical knowledge about images considered, we show that it is possible to discard some points before applying the Kadir detector by using Information Theory and...
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPCA) algorithm, recently proposed in the field of face recognition, in order to extract breast mass image features. In mammography, it is well known that the breast density measure is highly related to the risk of breast cancer...
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