Abstract: According to an exemplary embodiment, a method for pre-cropping digital image data includes: dividing the digital image into segments; computing a color value distance between corresponding pixels of neighboring segments of the digital image; comparing the color value distance(s) against a minimum color distance threshold; clustering neighboring segments having a color value distance less than or equal to the minimum color distance threshold; computing a connected structure based on the clustered segments; computing a polygon bounding the connected structure; comparing a fraction of segments included in the connected structure and the polygon, relative to a total number of segments in the digital image, to a minimum included segment threshold; and in response to determining the fraction of segments in the connected structure and the polygon, relative to the total number of segments meets or exceeds a minimum included segment threshold, cropping the digital image based on edges of the polygon.

Abstract: A method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.

Abstract: Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed. The concepts utilize internal features for detection and reconstruction, avoiding reliance on information derived from location of edges. The inventive concepts provide an improvement over conventional techniques since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, detecting a document depicted in a digital image includes: detecting a plurality of identifying features of the document, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of one or more edges of the document based at least in part on the plurality of identifying features; and outputting the projected location of the one or more edges of the document to a display of a computer, and/or a memory.

Abstract: Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image; optionally sampling color information from a second plurality of pixels of the digital image; generating or receiving a representative background color profile based on the color information sampled from the first plurality of pixels; generating or receiving a representative foreground color profile based on the color information sampled from the second plurality of pixels and/or the first plurality of pixels; assigning each pixel a label; binarizing the digital image based on the labels; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

Abstract: A method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.

Abstract: Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, reconstructing an object depicted in a digital image includes using a processor to: detect a plurality of identifying features of the object, where the identifying features are located internally with respect to the object; and reconstruct the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the identifying features.

Abstract: According to one aspect, a computer-implemented method of discovering processes for robotic process automation (RPA) includes: recording a plurality of event streams, each event stream corresponding to a human user interacting with a computing device to perform one or more tasks; concatenating the event streams; segmenting some or all of the concatenated event streams to generate one or more individual traces performed by the user interacting with the computing device, each trace corresponding to a particular task; clustering the traces according to a task type; identifying, from among some or all of the clustered traces, one or more candidate processes for robotic automation; prioritizing the candidate processes; and selecting at least one of the prioritized candidate processes for robotic automation. Further aspects building upon the above include generating RPA models to perform tasks determined to be processes for RPA. Corresponding systems and computer program products are also described.

Abstract: In various embodiments, computer program products for detecting, estimating, calculating, etc. characteristics of a document based on reference objects depicted on the document are disclosed. In one approach, a computer program product for processing a digital image depicting a document includes instructions executable by a computer for analyzing the digital image to determine one or more of a presence and a location of one or more reference objects; determining one or more geometric characteristics of at least one of the reference objects; defining one or more region(s) of interest based at least in part on one or more of the determined geometric characteristics; and detecting a presence or absence of an edge of the document within each defined region of interest. Additional embodiments leverage the type of document depicted in the image, multiple frames of image data, and/or calculate or extrapolate document edges rather than locating edges in the image.

Abstract: Computer program products for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer program product includes a computer readable medium having computer readable and/or executable program instructions embodied therewith, the program instructions being configured to cause a processor to: invoke a mobile application using a mobile device; receive auditory input via the mobile device; and perform a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.

Abstract: Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image; optionally sampling color information from a second plurality of pixels of the digital image; generating or receiving a representative background color profile based on the color information sampled from the first plurality of pixels; generating or receiving a representative foreground color profile based on the color information sampled from the second plurality of pixels and/or the first plurality of pixels; assigning each pixel a label; binarizing the digital image based on the labels; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

Abstract: Computerized techniques for real-time object detection from video data include: defining an analysis profile comprising an initial number of analysis cycles dedicated to each of a plurality of detectors, each detector being independently configured to detect objects according to a unique set of analysis parameters; receiving a plurality of frames of digital video data, the digital video data depicting an object; analyzing the plurality of frames using the plurality of detectors and in accordance with the analysis profile, wherein analyzing the plurality of frames produces an analysis result for each of the plurality of detectors; determining a confidence score for each of the analysis results; and updating the analysis profile by adjusting the number of analysis cycles dedicated to at least one of the plurality of detectors based on the confidence scores. Corresponding systems and computer program products are also disclosed.

Abstract: A method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.

Abstract: Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, reconstructing an object depicted in a digital image includes using a processor to: detect a plurality of identifying features of the object, where the identifying features are located internally with respect to the object; and reconstruct the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the identifying features.

Abstract: In one embodiment, a system includes: a processor; and logic in and/or executable by the processor to cause the processor to: generate a first feature vector based on a digital image captured by a mobile device; compare the first feature vector to a plurality of reference feature matrices; classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison; determine one or more object features of the object based at least in part on the particular object class; and detect one or more additional objects belonging to the particular object class based on the determined object feature(s). The one or more additional objects are depicted either in the digital image or another digital image received by the mobile device. Corresponding computer program products are also disclosed.

Abstract: Systems, computer program products, and techniques for reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be reconstructed even when edges are obscured or not depicted in the digital image data.

Abstract: According to one embodiment, a system includes a processor and logic in and/or executable by the processor to cause the processor to: initiate a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation; detect a document depicted in the video data; track a position of the detected document throughout the video data; select a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generate a composite image based on at least some of the selected plurality of images.

Abstract: Computer program products for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer program product includes a computer readable medium having computer readable and/or executable program instructions embodied therewith, the program instructions being configured to cause a processor to: invoke a mobile application using a mobile device; receive auditory input via the mobile device; and perform a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.

Abstract: In one embodiment, a method includes receiving a digital image captured by a mobile device; and using a processor of the mobile device: generating a first representation of the digital image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing; and determining one or more object features of the object based at least in part on the particular object class. Corresponding systems and computer program products are also disclosed.

Abstract: In various embodiments, methods, systems, and computer program products for determining distance between an object and a capture device are disclosed. The distance determination techniques are based on image data captured by the capture device, where the image data represent the object. These techniques improve the function of capture devices such as mobile phones by enabling determination of distance using a single lens capture device, and based on intrinsic parameters of the capture device, such as focal length and scaling factor(s), in preferred approaches. In some approaches, the distance estimation may be based in part on a priori knowledge regarding size of the object represented in the image data. Distance determination may be based on a homography transform and/or reference image data representing the object, a same type or similar type of object, in more approaches.

Abstract: Systems, methods, and computer program products are disclosed for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer-implemented method for performing a touchless mobile workflow includes: invoking a mobile application using a mobile device; receiving auditory input via the mobile device; and performing a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.