4,064 research outputs found
Geodesics on the manifold of multivariate generalized Gaussian distributions with an application to multicomponent texture discrimination
We consider the Rao geodesic distance (GD) based on the Fisher information as a similarity measure on the manifold of zero-mean multivariate generalized Gaussian distributions (MGGD). The MGGD is shown to be an adequate model for the heavy-tailed wavelet statistics in multicomponent images, such as color or multispectral images. We discuss the estimation of MGGD parameters using various methods. We apply the GD between MGGDs to color texture discrimination in several classification experiments, taking into account the correlation structure between the spectral bands in the wavelet domain. We compare the performance, both in terms of texture discrimination capability and computational load, of the GD and the Kullback-Leibler divergence (KLD). Likewise, both uni- and multivariate generalized Gaussian models are evaluated, characterized by a fixed or a variable shape parameter. The modeling of the interband correlation significantly improves classification efficiency, while the GD is shown to consistently outperform the KLD as a similarity measure
A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design
Audio fingerprinting, also named as audio hashing, has been well-known as a
powerful technique to perform audio identification and synchronization. It
basically involves two major steps: fingerprint (voice pattern) design and
matching search. While the first step concerns the derivation of a robust and
compact audio signature, the second step usually requires knowledge about
database and quick-search algorithms. Though this technique offers a wide range
of real-world applications, to the best of the authors' knowledge, a
comprehensive survey of existing algorithms appeared more than eight years ago.
Thus, in this paper, we present a more up-to-date review and, for emphasizing
on the audio signal processing aspect, we focus our state-of-the-art survey on
the fingerprint design step for which various audio features and their
tractable statistical models are discussed.Comment: http://www.iaria.org/conferences2015/PATTERNS15.html ; Seventh
International Conferences on Pervasive Patterns and Applications (PATTERNS
2015), Mar 2015, Nice, Franc
Multiscale Discriminant Saliency for Visual Attention
The bottom-up saliency, an early stage of humans' visual attention, can be
considered as a binary classification problem between center and surround
classes. Discriminant power of features for the classification is measured as
mutual information between features and two classes distribution. The estimated
discrepancy of two feature classes very much depends on considered scale
levels; then, multi-scale structure and discriminant power are integrated by
employing discrete wavelet features and Hidden markov tree (HMT). With wavelet
coefficients and Hidden Markov Tree parameters, quad-tree like label structures
are constructed and utilized in maximum a posterior probability (MAP) of hidden
class variables at corresponding dyadic sub-squares. Then, saliency value for
each dyadic square at each scale level is computed with discriminant power
principle and the MAP. Finally, across multiple scales is integrated the final
saliency map by an information maximization rule. Both standard quantitative
tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating
the proposed multiscale discriminant saliency method (MDIS) against the
well-know information-based saliency method AIM on its Bruce Database wity
eye-tracking data. Simulation results are presented and analyzed to verify the
validity of MDIS as well as point out its disadvantages for further research
direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio
Using segmented objects in ostensive video shot retrieval
This paper presents a system for video shot retrieval in which shots are retrieved based on matching video objects using a combination of colour, shape and texture. Rather than matching on individual objects, our system supports sets of query objects which in total reflect the user’s object-based information need. Our work also adapts to a shifting user information need by initiating the partitioning of a user’s search into two or more distinct search threads, which can be followed by the user in sequence. This is an automatic process which maps neatly to the ostensive model for information retrieval in that it allows a user to place a virtual checkpoint on their search, explore one thread or aspect of their information need and then return to that checkpoint to then explore an alternative thread. Our system is fully functional and operational and in this paper we illustrate several design decisions we have made in building it
Survey of Object Detection Methods in Camouflaged Image
Camouflage is an attempt to conceal the signature of a target object into the background image. Camouflage detection
methods or Decamouflaging method is basically used to detect foreground object hidden in the background image. In this
research paper authors presented survey of camouflage detection methods for different applications and areas
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