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Pedro Martins; Paulo Carvalho; Carlo Gatta |
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On the completeness of feature-driven maximally stable extremal regions |
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2016 |
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Pattern Recognition Letters |
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PRL |
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74 |
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9-16 |
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Local features; Completeness; Maximally Stable Extremal Regions |
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Abstract |
By definition, local image features provide a compact representation of the image in which most of the image information is preserved. This capability offered by local features has been overlooked, despite being relevant in many application scenarios. In this paper, we analyze and discuss the performance of feature-driven Maximally Stable Extremal Regions (MSER) in terms of the coverage of informative image parts (completeness). This type of features results from an MSER extraction on saliency maps in which features related to objects boundaries or even symmetry axes are highlighted. These maps are intended to be suitable domains for MSER detection, allowing this detector to provide a better coverage of informative image parts. Our experimental results, which were based on a large-scale evaluation, show that feature-driven MSER have relatively high completeness values and provide more complete sets than a traditional MSER detection even when sets of similar cardinality are considered. |
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Elsevier B.V. |
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0167-8655 |
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LAMP;MILAB; |
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Admin @ si @ MCG2016 |
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2748 |
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Author |
Pejman Rasti; Salma Samiei; Mary Agoyi; Sergio Escalera; Gholamreza Anbarjafari |
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Title |
Robust non-blind color video watermarking using QR decomposition and entropy analysis |
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Journal Article |
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2016 |
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Journal of Visual Communication and Image Representation |
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JVCIR |
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38 |
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838-847 |
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Video watermarking; QR decomposition; Discrete Wavelet Transformation; Chirp Z-transform; Singular value decomposition; Orthogonal–triangular decomposition |
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Abstract |
Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks. |
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HuPBA;MILAB; |
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Admin @ si @RSA2016 |
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2766 |
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Petia Radeva; J. Martinez; A. Tovar; X. Binefa; Jordi Vitria; Juan J. Villanueva |
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CORKIDENT: an automatic vision system for real-time inspection of natural products. |
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1999 |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ RMT1999 |
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23 |
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Petia Radeva; Jordi Vitria |
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Corkinspect: Statistical Learning of Natural Material |
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2004 |
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Italian Beverage Technology, 13(38):11–18 |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ RaV2004b |
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514 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Personalization and User Verification in Wearable Systems using Biometric Walking Patterns |
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2012 |
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Personal and Ubiquitous Computing |
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PUC |
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16 |
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5 |
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563-580 |
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In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies. |
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Springer-Verlag |
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1617-4909 |
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MILAB;HuPBA |
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Admin @ si @ CPR2012 |
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1706 |
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