Abstract: A method of controlling operation of an engine is provided that utilizes a number of preset operating parameters. The method determines an operating mode of the engine. The method determines an operating state of the engine. A plurality of engine parameter settings is retrieved from a memory in response to the determined operating mode and the determined operating state of the engine. The plurality of engine parameter settings are applied to at least one control algorithm of the engine.

Abstract: A method controlling operation of an engine utilizing a number of preset operating parameters is provided. An operating mode of the engine is determined. An operating state of the engine is determined. A first plurality of engine parameter settings are retrieved from a memory in response to the determined operating mode and the determined operating state of the engine. The first plurality of engine parameter settings are applied to at least one control algorithm of the engine. A rate of soot accumulation from the engine is monitored. The rate of soot accumulation is compared to a predetermined soot accumulation rate threshold. A second plurality of engine parameter settings are retrieved from a memory in response to the monitored rate of soot accumulation exceeding the predetermined soot accumulation rate threshold.

Abstract: A privacy-preserving multi-query parking management system and method. An image of a vehicle with respect to a specific part (e.g., license plate) can be captured when the vehicle enters via an entry point. An image signature can be computed by embedding the image into a descriptor space and the image signature can be stored in a database together with relevant metadata. An image of a vehicle with respect to the specific part can be captured when the vehicle exits via at least one exit point and an image signature can be computed. An entry-exit association with respect to the vehicle can be performed by searching for a most similar image signature in the database. Additionally, given a textual query (e.g., a license plate number), a signature can be computed by embedding the text into the same descriptor space.

Abstract: A system and method for classifying vehicles from laser scan data by receiving laser scan data corresponding to multiple vehicles from a laser scanner; extracting vehicle shapes corresponding to the multiple vehicles based on the laser scan data; aligning the vehicle shapes; and generating vehicle profiles based on the aligned vehicle shapes. The system and method can further include aligning the vehicle shapes using sequence kernels, such as global alignment kernels, and constraining the sequence kernels based on determined weights.

Abstract: A computer implemented method for localization of an object, such as a license plate, in an input image includes generating a task-dependent representation of the input image based on relevance scores for the object to be localized. The relevance scores are output by a classifier for a plurality of locations in the input image, such as patches. The classifier is trained on patches extracted from training images and their respective relevance labels. One or more similar images are identified from a set of images, based on a comparison of the task-dependent representation of the input image and task-dependent representations of images in the set of images. A location of the object in the input image is identified based on object location annotations for the similar images.

Abstract: A system and method enable generating a specific object detector for a category of interest. The method includes identifying seed objects in frames of a video sequence with a pre-trained generic detector for the category. An appearance model is iteratively learned for each of the seed objects using other frames in which the seed object is identified. The appearance models are learned jointly to optimize a loss function which accounts for the loss of incorrectly labeling sub-images and a regularization term which measures a distance between the appearance models. The loss of incorrectly labeling sub-images is determined using a motion model which predicts the location of the seed object in the subsequent frames so that sub-images outside the location that the current appearance model contribute to the loss. The specific object detector is then generated by aggregating the optimized appearance models.

Abstract: Methods and systems for detecting an object part location based on an extended date-driven detection. A specific relevance value between configurations of parts with respect to a set of training images annotated with annotating objects can be defined. A similarity learning algorithm can be applied with respect to the parts to obtain a similarity function based on the similarity between the part configurations. The similarity learning algorithm receives a set of positive pair having similar part configuration and a negative pair having different configuration and returns the similarity function that tends to assign a high score to new positive pair and a low score to negative pairs. A similarity between a new image and the training images can be measured utilizing the learned similarity function to obtain a neighbor image and a visible and/or non-visible part location with respect to the image can be predicted based on the neighbor image.

Abstract: A system and method enable generating a specific object detector for a category of interest. The method includes identifying seed objects in frames of a video sequence with a pre-trained generic detector for the category. An appearance model is iteratively learned for each of the seed objects using other frames in which the seed object is identified. The appearance models are learned jointly to optimize a loss function which accounts for the loss of incorrectly labeling sub-images and a regularization term which measures a distance between the appearance models. The loss of incorrectly labeling sub-images is determined using a motion model which predicts the location of the seed object in the subsequent frames so that sub-images outside the location that the current appearance model contribute to the loss. The specific object detector is then generated by aggregating the optimized appearance models.

Abstract: Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.

Abstract: An instance-level retrieval method and system are provided. A representation of a query image is embedded in a multi-dimensional space using a learned projection. The projection is learned using category-labeled training data to optimize a classification rate on the training data. The joint learning of the projection and the classifiers improves the computation of similarity/distance between images by embedding them in a subspace where the similarity computation outputs more accurate results. An input query image can thus be used to retrieve similar instances in a database by computing the comparison measure in the embedding space.

Abstract: It relates to spirocyclic compounds of formula (I), or pharmaceutically or veterinary acceptable salts thereof, or any stereoisomers either of the compounds of formula (I) or of their pharmaceutically or veterinary acceptable salts, wherein A and B form a spirocyclic ring system wherein the spiro atom connecting A and B is a carbon atom and wherein A is a known 3- to 8-membered carbocyclic or heterocyclic monocyclic ring or a known 6- to 18-membered carbocyclic or heterocyclic polycyclic ring system; B is a known 4- to 7-membered carbocyclic or heterocyclic monocyclic ring; C is phenyl or a known 5- to 6-membered heteroaromatic ring; and R1-R7 are as defined herein. It also relates to a process for their preparation, as well as to the intermediates used in this process; to pharmaceutical or veterinary compositions containing them, and to their use in medicine, in particular as antifibrinolytic and antihemorragic agents.

Abstract: A wireless telemetry system is proposed based on transmission of time reference for the monitoring of static and dynamic magnitudes. The proposed system comprises a reading instrument and, at least, a transponder which, in turn, includes the transducers associated to the variables object of observation and/or measurement. With the object of communicating the reading instrument and the transponder to each other, the system also comprises a mechanism for the transmission of information regarding the internal operating frequency of the transponder towards the reading instrument and a method for the remote determination of the internal operating frequency of the transponder. The reading instrument comprises: an antenna (11000), a communication section (12000), a signal processing section (13000), a computation section (14000), a timing unit (15000) stable with temperature, a user interface section (16000) and a data output section (17000).

Abstract: A method for recognition of an identifier such as a license plate includes storing first visual signatures, each extracted from a first image of a respective object, such as a vehicle, captured at a first location, and first information associated with the first captured image, such as a time stamp. A second visual signature is extracted from a second image of a second object captured at a second location and second information associated with the second captured image is acquired. A measure of similarity is computed between the second visual signature and at least some of the first visual signatures to identify a matching one. A test is performed, which is a function of the first and the second information associated with the matching signatures. Only when it is confirmed that the test has been met, identifier recognition is performed to identify the identifier of the second object.

Abstract: A system and method for comparing a text image and a character string are provided. The method includes embedding a character string into a vectorial space by extracting a set of features from the character string and generating a character string representation based on the extracted features, such as a spatial pyramid bag of characters (SPBOC) representation. A text image is embedded into a vectorial space by extracting a set of features from the text image and generating a text image representation based on the text image extracted features. A compatibility between the text image representation and the character string representation is computed, which includes computing a function of the text image representation and character string representation.

Abstract: Methods, systems and processor-readable media for vehicle classification. In general, one or more vehicles can be scanned utilizing a laser scanner to compile data indicative of an optical profile of the vehicle(s). The optical profile associated with the vehicle(s) is then pre-processed. Particular features are extracted from the optical profile following pre-processing of the optical profile. The vehicle(s) can be then classified based on the particular features extracted from the optical feature. A segmented laser profile is treated as an image and profile features that integrate the signal in one of the two directions of the image and Fisher vectors which aggregate statistics of local “patches” of the image are computed and utilized as part of the extraction and classification process.

Abstract: A system and a method for image segmentation use segmentation maps of one or more similar images as a basis for the segmentation. The method includes generating an image signature for an input image to be segmented and identifying at least one similar image from a set of images, based on the image signature of the input image and image signatures of images in the set of images. The similarity may be computed after first projecting the image signatures into a feature space where similarity is more likely to agree with segmentation map similarity. The input image is segmented, based on the segmentation map of one or more of the at least one identified similar images.

Abstract: A system and method for computing confidence in an output of a text recognition system includes performing character recognition on an input text image with a text recognition system to generate a candidate string of characters. A first representation is generated, based on the candidate string of characters, and a second representation is generated based on the input text image. A confidence in the candidate string of characters is computed based on a computed similarity between the first and second representations in a common embedding space.

Abstract: A system and method are provided for segmenting an image. The method includes computing an image signature for an input image. One or more similar images are identified from a first set of images, based on the image signature of the input image and image signatures of images in the first set of images. The similar image or images are used to define a cropped region of the input image and a second image signature is computed, this time for the cropped region. One or more similar images are identified from a second set of images, based on the cropped image signature and the image signatures of images in the second set of images. The input image is segmented based on a segmentation map of at least one of the similar images identified in the second set of images.

Abstract: A computer implemented method for localization of an object, such as a license plate, in an input image includes generating a task-dependent representation of the input image based on relevance scores for the object to be localized. The relevance scores are output by a classifier for a plurality of locations in the input image, such as patches. The classifier is trained on patches extracted from training images and their respective relevance labels. One or more similar images are identified from a set of images, based on a comparison of the task-dependent representation of the input image and task-dependent representations of images in the set of images. A location of the object in the input image is identified based on object location annotations for the similar images.

Abstract: Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.