Abstract: An exemplary baby diaper changing station (260) includes a table (264) that is configured to be in operative supported connection with a wall (262) through a pair of transversely disposed mounting brackets (266, 268). The table is in movable rotatable connection with the mounting brackets. The table is rotatably movable between a use position in which a generally planar changing surface (280) extends generally horizontal and faces upward, and a stored position in which the table extends parallel to the wall and in outwardly overlying relation of the mounting brackets. A pair of torsion springs (348) that are associated with respective joints (276, 278) operate to rotationally bias the table toward the stored position once the table has been rotationally moved by the user away from the use position.

Abstract: An approach is provided for an asymmetric evaluation of polygon similarity. The approach, for instance, involves receiving a first polygon representing an object depicted in an image. The approach also involves generating a transformation of the image comprising image elements whose values are based on a respective distance that each image element is from a nearest image element located on a first boundary of the first polygon. The approach further involves determining a subset of the plurality of image elements of the transformation that intersect with a second boundary of a second polygon. The approach further involves calculating a polygon similarity of the second polygon with respect the first polygon based on the values of the subset of image elements normalized to a length of the second boundary of the second polygon.

Abstract: Systems and methods for correcting mapping information inaccuracies are described. In some aspects, the method includes receiving terrestrial data captured in an area of interest, and detecting features in the terrestrial data identifying ground points in the area of interest. The method also includes correlating the ground points with ground control points in the area of interest to determine a correspondence, and computing an aggregate of positional differences between corresponding points. The method further includes generating a report indicating a quality of the terrestrial data captured in the area of interest based on the aggregate.

Abstract: A method is provided for generating and revising map geometry based on a received image and probe data. A method may include: receiving probe data from a first period of time, where the probe data from a first period of time is from a plurality of probes within a predefined geographic region; generating a first image of the predefined geographic region based on the probe data from the first period of time; receiving probe data from a second period of time different from the first period of time, where the probe data from the second period of time is from a plurality of probes within the predefined geographic region; generating a second image based on the probe data from the second period of time; comparing the first image to the second image; and generating a revised route geometry based on changes detected between the first image and the second image.

Abstract: An approach is provided for image labeling for cross view alignment. The approach, for example, involves determining camera pose data, camera trajectory data, or a combination thereof for a first image depicting an area from a first perspective view. The approach also involves processing the camera pose data, the camera trajectory data, or a combination thereof to generate meta data indicating a position, an orientation, or a combination thereof of the first perspective view of the area relative to a second image depicting the area from a second perspective view. The approach further involves providing data for presenting the meta data in a user interface as an overlay on the second perspective view.

Abstract: An approach is provided for a redundant feature detection engine. The approach, for instance, involves segmenting an input image into a plurality of grid cells for processing by the redundant feature detection engine. The redundant feature detection engine includes a neural network. The approach also involves, for each of the plurality of grid cells, initiating a prediction of an object code by the redundant feature detection engine. The object code is a predicted feature that uniquely identifies an object depicted in the input image. The approach further involves aggregating the plurality of grid cells into one or more clusters based on the object code predicted for said each grid cell. The approach further involves predicting one or more features of the object corresponding to a respective cluster of the one or more clusters by merging one or more feature prediction outputs of said each grid cell in the respective cluster.

Abstract: An approach is provided for a location-aware evaluation of a machine learning model. The approach, for example, involves designating a geographic area for creating an evaluation dataset for the machine learning model. The approach also involves separating a plurality of observation data records into the evaluation dataset and a training dataset based on a comparison of a respective data collection location of each of the plurality of observation data records to the geographic area. The training dataset is then used to train the machine learning model, and the evaluation dataset is used to evaluate the trained machine learning model.

Abstract: A method, apparatus and computer program product are provided for identifying potential correspondence between image points and using clustering and filtering to generate consistent three-dimensional points of correspondence between two-dimensional images.

Abstract: A method, apparatus and computer program product are provided for establishing correspondences between images using through generation of a translation between the different perspectives. Methods may include: receiving first sensor data from a first image sensor, where the first sensor data includes a first image of an environment captured from a first perspective; receiving second sensor data from a second image sensor of a second image of the environment captured from a second perspective; identifying image correspondence points between the first sensor data and the second sensor data; computing pairwise vectors between corresponding pairs of first projected points of the first sensor data and second projected points of the second sensor data; clustering the pairwise vectors according to magnitude and orientation; and generating a translation vector from clusters of pairwise vectors, where the translation vector represents a shift of the second image sensor data to correspond to ground truth data.

Abstract: The disclosure provides methods, apparatus, and products for attention guidance and labeling. In one aspect, a method comprises receiving metadata associated with a perspective image captured by an image capture device located at the image position and having the image pose, wherein the metadata comprises the image position and the image pose. The method comprises defining a field-of-view indicator having a first indicator position located at the image position and having the image pose; receiving ground control point (GCP) information identifying a GCP, wherein the GCP information comprises a GCP position; defining a GCP indicator having a second indicator position located at the GCP position; and causing display of an indicator layer comprising the field-of-view indicator and the GCP indicator in a second portion of an interactive user interface (IUI) of a labeling tool, wherein at least the perspective image is displayed in a first portion of the IUI.

Abstract: A method includes obtaining an object comprising a plurality of images, each image comprising at least one of: one or more tie points or one or more stray points. The method also includes determining an importance score of each tie point of the one or more tie points in the images. The method also includes determining an importance score of each stray point of the one or more stray points in the images. The method also includes determining an importance score of the object based on the importance score of the one or more tie points and the importance score of the one or more stray points. The method also includes providing the importance score of the object as an output for selection of the object for image labeling.

Abstract: An approach is provided for determining a polygon of a geographic database that overlaps a candidate polygon or candidate point. The geographic database represents stored polygons as respective polygon points with zero area. The approach involves determining proximate polygon points from among the respective polygon points with zero area that are within a distance threshold of the candidate polygon or the candidate point. The approach also involves retrieving one or more proximate polygons from the geographic database that correspond to the one or more proximate polygon points. The approach further involves determining an intersection between the one or more proximate polygons and the candidate polygon or the candidate point. The approach then involves selecting the polygon that overlaps the candidate polygon or the candidate point based on the determined intersection.

Abstract: The disclosure provides methods, apparatus, and products for attention guidance and labeling. In one aspect, a method comprises receiving metadata associated with a perspective image captured by an image capture device located at the image position and having the image pose, wherein the metadata comprises the image position and the image pose. The method comprises defining a field-of-view indicator having a first indicator position located at the image position and having the image pose; receiving ground control point (GCP) information identifying a GCP, wherein the GCP information comprises a GCP position; defining a GCP indicator having a second indicator position located at the GCP position; and causing display of an indicator layer comprising the field-of-view indicator and the GCP indicator in a second portion of an interactive user interface (IUI) of a labeling tool, wherein at least the perspective image is displayed in a first portion of the IUI.

Abstract: The disclosure provides methods, apparatus, and products for attention guidance and labeling. In one aspect, a method comprises receiving metadata associated with a first perspective image captured by a first image capture device located at a first image position and having a first image pose, wherein the metadata comprises the first image position and first image pose; defining a first field-of-view indicator; receiving metadata associated with a second perspective image captured by a second image capture device located at a second image position and having a second image pose, wherein the metadata comprises the second image position and second image pose; defining a second field-of-view indicator; and causing display of an indicator layer comprising the first and second field-of-view indicators in a second portion of an IUI of a labeling tool, wherein at least the first or second perspective image is displayed in a first portion of the IUI.

Abstract: An approach is provided for location correction using feature point correspondences between images or image sources. The approach, for example, involves processing a first image and a second image to identify a feature that is visible in both the first image and the second image. The first image has an image-to-ground correspondence between the feature in the first image and a geographic location. The approach also involves transferring the image-to-ground correspondence from the first image to the second image. The approach further involves using the transferred image-to-ground correspondence to reference the feature in the second image to the geographic location.

Abstract: An approach is provided for determining a ground control point from image data using machine learning. The approach, for example, involves selecting an feature based determining that the feature meets one or more properties for classification as a machine learnable feature. The approach also involves retrieving a plurality of ground truth images depicting the feature. The plurality of ground truth images is labeled with known pixel location data of the feature as respectively depicted in each of the plurality of ground truth images. The approach further involves training a machine learning model using the plurality of ground truth images to identify predicted pixel location data of the ground control point as depicted in an input image.

Abstract: An approach is provided for generating a polyline from line segments (e.g., line segments representing objects detected by a computer vision system). The approach involves selecting a line segment from a plurality of line segments. The approach also involves determining a neighboring line segment from among the plurality of line segments. The determined neighboring line segment has a closest distance to the line segment from among the plurality of line segments. The approach further involves merging the line segment and the neighboring line segment into a polyline based on determining that the closest distance is a mutual closest distance between line segment and the neighboring line segment.

Abstract: An approach is provided for detecting degraded ground paint in an image. The approach, for example, involves performing semantic segmentation on the image to determine one or more pixels of the image that are classified in a ground paint category. The approach also involves generating a binary image that contains the one or more pixels of the image that are classified in the ground paint category. The approach further involves generating a hole-filled binary image by filling in the binary image to generate one or more curvilinear structures from the one or more pixels. The approach further involves determining a difference between the image and the hole-filled binary image to identify one or more degraded ground paint pixels of the image and providing the one or more degraded ground paint pixels as an output.

Abstract: An approach is provided for determining a feature correspondence based on camera geometry. The approach, for example, involves determining a first labeled or detected pixel location in a first image and a second labeled or detected pixel location in a second image. The approach also involves computing a first ray from a first camera position of the first image through the first labeled or detected pixel location. The approach further involves computing a second ray from a second camera position of the second image through the second labeled or detected pixel location. The approach further involves computing a closeness value of the first ray and the second ray. The approach further involves providing an output indicating the feature correspondence between the first labeled or detected pixel location and the second labeled or detected pixel location based on determining that the closeness value is within a threshold value.

Abstract: Systems and methods for correcting mapping information inaccuracies are provided. In some aspects, the method includes receiving terrestrial data captured in an area of interest, and detecting features in the terrestrial data identifying ground points in the area of interest. The method also includes correlating the ground points with ground control points in the area of interest to determine a correspondence, and computing an aggregate of positional differences between corresponding points. The method further includes generating a report indicating a quality of the terrestrial data captured in the area of interest based on the aggregate.