Abstract: A method for producing 3D multi-view visual contents including capturing a visual scene from at least one first point of view for generating a first bidimensional image of the scene and a corresponding first depth map indicative of a distance of different parts of the scene from the first point of view. The method further includes capturing the visual scene from at least one second point of view for generating a second bidimensional image; processing the first bidimensional image to derive at least one predicted second bidimensional image predicting the visual scene captured from the at least one second point of view; deriving at least one predicted second depth map predictive of a distance of different parts of the scene from the at least one second point of view by processing the first depth map, the at least one predicted second bidimensional image and the second bidimensional image.

Abstract: An automated emotional recognition system is adapted to determine emotional states of a speaker based on the analysis of a speech signal. The emotional recognition system includes at least one server function and at least one client function in communication with the at least one server function for receiving assistance in determining the emotional states of the speaker. The at least one client function includes an emotional features calculator adapted to receive the speech signal and to extract therefrom a set of speech features indicative of the emotional state of the speaker. The emotional state recognition system further includes at least one emotional state decider adapted to determine the emotional state of the speaker exploiting the set of speech features based on a decision model. The server function includes at least a decision model trainer adapted to update the selected decision model according to the speech signal.

Abstract: A method for compressing data, the data being represented by an input vector having Q features, wherein Q is an integer higher than 1, including the steps of 1) providing a vector codebook of sub-sets of indexed Q-feature reference vectors and threshold values associated with the sub-sets for a prefixed feature; 2) identifying a sub-set of reference vectors among the sub-sets by progressively comparing the value of a feature of the input vector which corresponds to the prefixed feature, with the threshold values associated with the sub-sets; and 3) identifying the reference vector which, within the sub-set identified in step 2), provides the lowest distortion with respect to the input vector.

Abstract: A method for producing 3D multi-view visual contents including capturing a visual scene from at least one first point of view for generating a first bidimensional image of the scene and a corresponding first depth map indicative of a distance of different parts of the scene from the first point of view. The method further includes capturing the visual scene from at least one second point of view for generating a second bidimensional image; processing the first bidimensional image to derive at least one predicted second bidimensional image predicting the visual scene captured from the at least one second point of view; deriving at least one predicted second depth map predictive of a distance of different parts of the scene from the at least one second point of view by processing the first depth map, the at least one predicted second bidimensional image and the second bidimensional image.

Abstract: An automated emotional recognition system is adapted to determine emotional states of a speaker based on the analysis of a speech signal. The emotional recognition system includes at least one server function and at least one client function in communication with the at least one server function for receiving assistance in determining the emotional states of the speaker. The at least one client function includes an emotional features calculator adapted to receive the speech signal and to extract therefrom a set of speech features indicative of the emotional state of the speaker. The emotional state recognition system further includes at least one emotional state decider adapted to determine the emotional state of the speaker exploiting the set of speech features based on a decision model. The server function includes at least a decision model trainer adapted to update the selected decision model according to the speech signal.

Abstract: An automated emotional recognition system includes an emotional state classifier adapted to receive, during an operative phase, an input information stream with embedded information related to emotional states of a person, and to generate a succession of emotional state indications derived from the input information stream. The emotional recognition system further includes a post-processing function, configured to receive at least two emotional state indications of the succession and, for each of said at least two emotional state indications, determine a corresponding emotional state representation in an emotional state representation system. The post-processing function is further configured to combine the emotional state representations of the at least two emotional state indications to obtain an output emotional state indication.

Abstract: A filter such as a Wiener filter for noise reduction in a signal, such as a speech signal, affected by background noise includes a circuit for determining values of an update function relating new value of estimated noise power to a previous value of estimated noise power, the update function being a function of said previous estimated noise power and a mean input power spectral density. The circuit includes a look-up table having values for the update function stored therein with the previous value of estimated noise power and the mean input power spectral density as a first and a second search entry, respectively. These search entries are entered via an input module and exploited by search circuitry associated with the look-up table for selectively searching values for the update function in the look-up table. The search is preferably carried out on the basis of an index computed starting from said first and second search entries.

Abstract: A method for compressing data, the data being represented by an input vector having Q features, wherein Q is an integer higher than 1, including the steps of 1) providing a vector codebook of sub-sets of indexed Q-feature reference vectors and threshold values associated with the sub-sets for a prefixed feature; 2) identifying a sub-set of reference vectors among the sub-sets by progressively comparing the value of a feature of the input vector which corresponds to the prefixed feature, with the threshold values associated with the sub-sets; and 3) identifying the reference vector which, within the sub-set identified in step 2), provides the lowest distortion with respect to the input vector.

Abstract: The present invention relates to a module 50 for generating integrated decoding circuits for use, in particular, in turbo devices, to the method for defining the characteristics of and generating convolutional decoding circuits, and to the circuit that can be obtained with said module 50. The module 50 is parametric and, thanks to this feature, makes it possible to generate decoding circuits having different performance characteristics which are such that they can be used in turbo devices employing different decoding modes and different architectures. In addition, the module 50 makes it possible to generate decoding circuits whose distinguishing feature is that they can manage a plurality of generator polynomials selectively and can thus also be used in asymmetrical turbo devices.

Abstract: A filter such as a Wiener filter for noise reduction in a signal, such as a speech signal, affected by background noise includes a circuit for determining values of an update function relating new value of estimated noise power to a previous value of estimated noise power, the update function being a function of said previous estimated noise power and a mean input power spectral density. The circuit includes a look-up table having values for the update function stored therein with the previous value of estimated noise power and the mean input power spectral density as a first and a second search entry, respectively. These search entries are entered via an input module and exploited by search circuitry associated with the look-up table for selectively searching values for the update function in the look-up table. The search is preferably carried out on the basis of an index computed starting from said first and second search entries.

Abstract: The present invention relates to a method for obtaining electronic circuits wherein the design steps (100) constituted by a first development and testing cycle (200), of the functional type, and a second development and testing cycle (300), of the architectural type, are managed using, as inputs, for both cycles (200 and 300) the same configuration files (140) and stimuli (150) and generating, at the output, results having equivalent (230, 330) and comparable (333) formats. Thanks to these characteristics, it is possible to conduct in integrated fashion functional tests (220) and architectural tests (320) on corresponding functional and architectural models of electronic circuits and verify the perfect correspondence between the different types of models as the configurations files (140) and stimuli (150) vary.

Abstract: The present invention relates to a module 50 for generating integrated decoding circuits for use, in particular, in turbo devices, to the method for defining the characteristics of and generating convolutional decoding circuits, and to the circuit that can be obtained with said module 50. The module 50 is parametric and, thanks to this feature, makes it possible to generate decoding circuits having different performance characteristics which are such that they can be used in turbo devices employing different decoding modes and different architectures. In addition, the module 50 makes it possible to generate decoding circuits whose distinguishing feature is that they can manage a plurality of generator polynomials selectively and can thus also be used in asymmetrical turbo devices.

Abstract: This invention refers to a module 10 for generating integrated circuits suitable for analysing and validating bit strings inside telecommunications data cells, to the method for defining the structure and characteristics of such module and the integrated circuits that can be generated and to the integrated circuit that can be obtained with such module 10. The module 10, called parser, is parametric and makes it possible to generate parser circuits for many protocols because of such characteristic; the module 10, also, makes it possible, by means of a module REGFILE_2OUT 12, to generate programmable parser circuits and, by means of a module LOGIC_OPER 22 that can generate several analysis and validation devices, to execute in parallel bit string analysis inside telecommunications data cells.

Abstract: Models destined for verification are described at the level of synthesizable description (for example VHDL). The synthesizable description (200) is automatically converted (300) into a C++ model (200′). This allows verification of the correctness of the synthesizable description by comparing the results of a verification carried out on the original description from the cell in C++ with the results of a similar verification of the C++ model obtained by automatic conversion of the synthesizable description. It is also possible to make the C++ model obtained by automatic conversion (200′) to interact with a system model including blocks (201, 202, 203) of a system model at C++ level, in particular with the possibility of producing concurrent events that occur in correspondence with a main timing signal source.

Abstract: The circuit for motion estimation in digitised video sequence encoders comprises at least an integrated circuit component (IM, IM1 . . . IMn) which is arranged to perform either the function of determining motion vectors and associated costs for different prediction modes, or the function of vector refinement, possibly in addition to prediction mode selection. The circuit (IM) is based on the use of two operating units (M1, M2) which are arranged to concurrently process in different ways different pixel groups according to a MIMD technique. Preferably, when the circuit performs motion vector determination, the operating units (M1, M2) are programmed to execute a genetic algorithm exploiting an initial vector population taking into account the temporal and spatial correlations in the picture.