Abstract: A refuse vehicle includes a chassis, an energy storage device supported by the chassis and configured to provide electrical power to a prime mover, wherein activation of the prime mover selectively drives the refuse vehicle, a body for storing refuse therein supported by the chassis, a first hydraulic pump configured to convert electrical power into hydraulic power, a second first hydraulic pump configured to convert electrical power into hydraulic power, and a motor coupled to at least one of the body or the chassis and configured to drive the first hydraulic pump and drive the second hydraulic pump.

Abstract: Described herein is a method of generating an image that includes receiving a set of data corresponding to an object. The method also includes generating a three-dimensional representation of the object using the set of data. The method includes generating properties for the object using the set of data. The method also includes associating the properties with the three-dimensional representation of the object, wherein the three-dimensional representation of the object and the properties for the object are used to produce training data for an object recognition algorithm.

Abstract: A method for co-registering terrain data and image data includes receiving terrain data and image data. The method also includes determining a position of a light source based upon the image data. The method also includes creating a hillshade representation of the terrain data based upon the terrain data and the position of the light source. The method also includes identifying a portion of the hillshade representation and a portion of the image data that correspond to one another. The method also includes comparing the portion of the hillshade representation and the portion of the image data. The method also includes determining a vector control between the portion of the hillshade representation and the portion of the image data based upon the comparison. The method also includes applying the vector control to the image data to produce updated image data.

Abstract: A method for co-registering terrain data and image data includes receiving terrain data and image data. The method also includes determining a position of a light source based upon the image data. The method also includes creating a hillshade representation of the terrain data based upon the terrain data and the position of the light source. The method also includes identifying a portion of the hillshade representation and a portion of the image data that correspond to one another. The method also includes comparing the portion of the hillshade representation and the portion of the image data. The method also includes determining a vector control between the portion of the hillshade representation and the portion of the image data based upon the comparison. The method also includes applying the vector control to the image data to produce updated image data.

Abstract: A method and apparatus for simulating spectral representation of a region of interest is disclosed. In one embodiment, the method comprises determining a physical characteristic of a geospatial portion of the region of interest, associating the determined physical characteristic with a material of a spectral library, the spectral library having at least one spectral definition material, associating the spectral definition of the material with the geospatial portion of the region of interest, wherein the material is at least partially representative of the geospatial section of the region of interest, and generating the simulated spectral representation of the region of interest at least in part from at least the associated spectral definition of the at least one material.

Abstract: A system and method for collecting spectral data of a region of interest with a sensor is described. In one embodiment, the method comprises generating a simulated spectral representation of a region of interest, identifying at least one of the plurality of materials as a material of interest within the region of interest, identifying other of the plurality of materials not identified as a material of interest as background materials within the region of interest, selecting a subset spectral portion of the spectral data according to the simulated spectral representation of the material of interest and the simulated spectral representation of the background materials within the region of interest, and configuring the sensor to collect a subset spectral portion of the spectral data.

Abstract: Currency bills are transported past an image scanner to one or more output receptacles. Each of the bills is imaged to produce image data from which a visually readable image of each bill can be reproduced. The serial number, denomination, and/or secondary identifiers of a bill is attempted to be extracted and/or determined from the image data associated with the bill. The serial number of the bill has an integer number, X, of characters. One or more of the X characters of the serial number of the currency bill is not extracted with a predetermined confidence. In response to failing to extract all of the X characters of the serial number of the bill with the predetermined confidence, a serial number field in an electronic record associated with the bill is populated with a serial number snippet image. The electronic record is stored in a non-transitory memory.

Abstract: A method of implementing a self-calibrating database of spectral data includes receiving remotely-sensed spectral data for a geographic location. The method also includes accessing spectral data for a composition of materials at the geographic location from a database of spectral data for compositions of materials at respective geographic locations. The method includes calibrating the spectral data to match the remotely-sensed spectral data and thereby produce calibrated spectral data for the composition. The method includes validating the calibrated spectral data for the composition. And in an instance in which the calibrated spectral data for the composition is validated, the method includes replacing the spectral data with the calibrated spectral data to produce an enhanced database of spectral data for use in identifying materials or compositions of materials therefrom; and in at least one instance, outputting identifiers of the materials in the composition of materials.

Abstract: Described herein is a method of generating an image that includes receiving a set of data corresponding to an object. The method also includes generating a three-dimensional representation of the object using the set of data. The method includes generating properties for the object using the set of data. The method also includes associating the properties with the three-dimensional representation of the object, wherein the three-dimensional representation of the object and the properties for the object are used to produce training data for an object recognition algorithm.

Abstract: A method of identifying a target material in a spectral image includes acquiring a spectral image of a scene. The method also includes performing image segmentation to partition the spectral image into a plurality of segments. The method includes accessing a database of spectral models of a plurality of materials to determine a material whose spectral model is most similar to the spectral data for the segment, a difference between the spectral model of the material and the spectral data for the segment including measurable reflectance or radiance at characteristic frequencies or wavelengths. The method also includes analyzing a database of spectral data for a plurality of target materials to identify a target material whose spectral data also has measurable reflectance or radiance at the characteristic frequencies or wavelengths. And the method includes outputting an identifier of the target material for display with the spectral image.

Abstract: An example method includes determining first classification rule(s) based on first data that classifies pixel groups of first reference image(s) as types of objects. The first reference image(s) are captured by a first sensor. The method further includes determining second classification rule(s) based on second data that classifies pixel groups of second reference image(s) as types of objects. The second reference image(s) are captured by a second sensor. The method includes classifying, as respective first objects, pixel group(s) of a first image of a scene based on the first classification rule(s). The method includes classifying, as respective second objects, pixel group(s) of a second image of the scene based on the second classification rule(s). The method further includes determining whether a change occurred in the scene based on the object classification of the first image(s) and the second image(s).

Abstract: A method and apparatus is provided for forming a model of a structure. Input data comprising a set of values for a set of attributes is received. The set of values for the set of attributes is matched to a number of texture decks in a plurality of texture decks. A texture deck in the plurality of texture decks is associated with a set of assigned attributes. Each assigned attribute in the set of assigned attributes is assigned at least one assigned value. A texture deck from the number of texture decks is selected as a final texture deck for use in forming the model of the structure.

Abstract: A method of implementing a self-calibrating database of spectral data includes receiving remotely-sensed spectral data for a geographic location. The method also includes accessing spectral data for a composition of materials at the geographic location from a database of spectral data for compositions of materials at respective geographic locations. The method includes calibrating the spectral data to match the remotely-sensed spectral data and thereby produce calibrated spectral data for the composition. The method includes validating the calibrated spectral data for the composition. And in an instance in which the calibrated spectral data for the composition is validated, the method includes replacing the spectral data with the calibrated spectral data to produce an enhanced database of spectral data for use in identifying materials or compositions of materials therefrom; and in at least one instance, outputting identifiers of the materials in the composition of materials.

Abstract: A method of identifying a target material in a spectral image includes acquiring a spectral image of a scene. The method also includes performing image segmentation to partition the spectral image into a plurality of segments. The method includes accessing a database of spectral models of a plurality of materials to determine a material whose spectral model is most similar to the spectral data for the segment, a difference between the spectral model of the material and the spectral data for the segment including measurable reflectance or radiance at characteristic frequencies or wavelengths. The method also includes analyzing a database of spectral data for a plurality of target materials to identify a target material whose spectral data also has measurable reflectance or radiance at the characteristic frequencies or wavelengths. And the method includes outputting an identifier of the target material for display with the spectral image.

Abstract: A system and method for surveying a region of interest with a mobile platform having a sensor having a plurality of narrow spectral bands spanning a contiguous frequency space is disclosed. In one embodiment, the method comprises generating a simulated spectral representation of a region of interest, identifying at least one of the plurality of materials as a material of interest within the region of interest, identifying other of the plurality of materials not identified as a material of interest as background materials within the region of interest, sensing, with the sensor, spectral data in the region of interest in the plurality of narrow spectral bands, selecting and transmitting only the spectral data of the one of more of the plurality of spectral bands of the sensor according to the simulated spectral representation of the material of interest.

Abstract: Currency bills are transported past an image scanner to one or more output receptacles. Each of the bills is imaged to produce image data from which a visually readable image of each bill can be reproduced. The serial number, denomination, and/or secondary identifiers of a bill is attempted to be extracted and/or determined from the image data associated with the bill. The serial number of the bill has an integer number, X, of characters. One or more of the X characters of the serial number of the currency bill is not extracted with a predetermined confidence. In response to failing to extract all of the X characters of the serial number of the bill with the predetermined confidence, a serial number field in an electronic record associated with the bill is populated with a serial number snippet image. The electronic record is stored in a non-transitory memory.

Abstract: Currency bills are transported past an image scanner to one or more output receptacles. Each of the bills is imaged to produce image data from which a visually readable image of each bill can be reproduced. The serial number, denomination, and/or secondary identifiers of a bill is attempted to be extracted and/or determined from the image data associated with the bill. The serial number of the bill has an integer number, X, of characters. One or more of the X characters of the serial number of the currency bill is not extracted with a predetermined confidence. In response to failing to extract all of the X characters of the serial number of the bill with the predetermined confidence, a serial number field in an electronic record associated with the bill is populated with a serial number snippet image. The electronic record is stored in a non-transitory memory.

Abstract: An example method includes determining first classification rule(s) based on first data that classifies pixel groups of first reference image(s) as types of objects. The first reference image(s) are captured by a first sensor. The method further includes determining second classification rule(s) based on second data that classifies pixel groups of second reference image(s) as types of objects. The second reference image(s) are captured by a second sensor. The method includes classifying, as respective first objects, pixel group(s) of a first image of a scene based on the first classification rule(s). The method includes classifying, as respective second objects, pixel group(s) of a second image of the scene based on the second classification rule(s). The method further includes determining whether a change occurred in the scene based on the object classification of the first image(s) and the second image(s).

Abstract: A system and method for collecting spectral data of a region of interest with a sensor is described. In one embodiment, the method comprises generating a simulated spectral representation of a region of interest, identifying at least one of the plurality of materials as a material of interest within the region of interest, identifying other of the plurality of materials not identified as a material of interest as background materials within the region of interest, selecting a subset spectral portion of the spectral data according to the simulated spectral representation of the material of interest and the simulated spectral representation of the background materials within the region of interest, and configuring the sensor to collect a subset spectral portion of the spectral data.

Abstract: A method and apparatus for simulating spectral representation of a region of interest is disclosed. In one embodiment, the method comprises determining a physical characteristic of a geospatial portion of the region of interest, associating the determined physical characteristic with a material of a spectral library, the spectral library having at least one spectral definition material, associating the spectral definition of the material with the geospatial portion of the region of interest, wherein the material is at least partially representative of the geospatial section of the region of interest, and generating the simulated spectral representation of the region of interest at least in part from at least the associated spectral definition of the at least one material.