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This paper presents an embedded facial image analysis framework based on Convolutional Neural Networks (ConvNets). This robust framework has been proposed by Garcia, Delakis and Duffner on general purpose workstations without any constraints on computational and memory resources. We show that ConvNets, which consist of a pipeline of convolution and subsampling operations followed by a Multi Layer...
Current object detection systems reach high detection rates, at the expense of requiring a large training database. This paper presents a new method for object detection, that gives state-of-the-art results, while using a reduced training database. The proposed system relies on a new local feature extraction approach inspired by Convolutional Neural Networks, Principal Component Analysis and Multilayer...
In this work, the Full-Wavelet Region of Interest Extraction Method (FWREM) is explained, where a ROI (Region of Interest) in a image can be accessed with a unique representation space, avoiding additional processing over the Image Space, in order to preserve the quality of desired details. In this case, a Region of Interest can be displayed, with the same perceived-distortion features, but with features...
The determination of right boundaries during phoneme segmentation of a speech signal is an important part in the process of automatic speech recognition. However, when no information is provided about the meaning of the signal, this segmentation process becomes very difficult. Currently, most of the methods used to detect boundaries of phonemes are based in the identification of variations in distances...
This study addresses the advantage of adding quality information of the biometric signals into a multimedia-based (video and audio) identity verification system. The quality information of the biometric signals can be used in several ways and stages in the biometric system. In this study, the authors introduce quality-based decisions in two stages: score normalisation and frame selection. Quality-based...
Image remote access using cache strategies has been considered, in order to improve decoding times. However, wavelet coefficients used in coding are not the optimal solution for the Rate-Distortion functional optimization. Directional wavelet filters have shown as good candidates for setting up the Lp space for edge and contour approximation of image tiling and Windows of Interest, and are analyzed...
In this paper, we propose a novel method for robustly classifying visual concepts. In order to achieve this aim, we propose a scheme that relies on Self Organizing Maps (SOM [6]). Heterogeneous local signatures are first extracted from training images and projected into specialized SOM networks. The extracted signatures activate several neural maps producing activation histograms. These activation...
We present a novel approach for face recognition based on salient singularity descriptors. The automatic feature extraction is performed thanks to a salient point detector, and the singularity information selection is performed by a SOM region-based structuring. The spatial singularity distribution is preserved in order to activate specific neuron maps and the local salient signature stimuli reveals...
In this paper, a high-level optimization methodology is applied for the implementation of the well-known convolutional face finder (CFF) algorithm for real-time applications on cellular phone, such as teleconferencing, advanced user interfaces, pictures indexing and security access control. This face detector is based on a feature extraction and classification technique which consists in a pipeline...
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