Reducing false detections in template-based classification of identity documents. In an embodiment, an iterative procedure is used to generate one or more hypotheses for the location of a document in image data and a type of document in the image data based on a plurality of predefined models representing a plurality of types of documents. The one or more hypotheses are filtered by rejecting any hypothesis that is not well-conditioned according to one or more criteria. When a best hypothesis that satisfies a threshold remains after filtering the one or more hypotheses, the document in the image data is analyzed, and, when no hypothesis that satisfies the threshold remains after filtering the one or more hypotheses, the image data is rejected.

A method, system and computer-readable storage medium for performing a cognitive information processing operation. The cognitive information processing operation includes: receiving data from a plurality of data sources; processing the data from the plurality of data sources to provide cognitively processed insights via an augmented intelligence system, the augmented intelligence system executing on a hardware processor of an information processing system, the augmented intelligence system and the information processing system providing a cognitive computing function; performing a robustness assessment operation, the robustness assessment operation assessing robustness of the cognitive computing function, the robustness assessment operation generating a robustness score representing robustness of the cognitive computing function; and, providing the cognitively processed insights to a destination, the destination comprising a cognitive application, the cognitive application enabling a user to interact with the cognitive insights.

Systems and methods of the present disclosure provide an improved approach for open-set instance segmentation by identifying both known and unknown instances in an environment. For example, a method can include receiving sensor point cloud input data including a plurality of three-dimensional points. The method can include determining a feature embedding and at least one of an instance embedding, class embedding, and/or background embedding for each of the plurality of three-dimensional points. The method can include determining a first subset of points associated with one or more known instances within the environment based on the class embedding and the background embedding associated with each point in the plurality of points. The method can include determining a second subset of points associated with one or more unknown instances within the environment based on the first subset of points. The method can include segmenting the input data into known and unknown instances.

Disclosed herein are methods and systems that allow users to report traffic violations and obtain information concerning reported violations using mobile devices. In one embodiment, a method comprises receiving, at a server, one or more images or videos captured by a mobile device of an offending vehicle committing a potential traffic violation and an extended metadata tag; storing the one or more images or videos and the extended metadata tag as unstructured content in a content lake; generating database tables on top of the content lake; receiving a request from another mobile device to view traffic violation content; querying the database tables and retrieving at least one of the one or more images or videos of the offending vehicle committing the potential traffic violation from the content lake; and generating a GUI to be displayed via the other mobile device showing the traffic violation content.

The present disclosure proposes a computer implemented of object recognition of an object to be identified using a method for reconstruction of a 3D point cloud. The method comprises the steps of acquiring, by a mobile device, a plurality of pictures of said object, sending the acquired pictures to a cloud server, reconstructing, by the cloud server, a 3D points cloud reconstruction of the object, performing a 3D match search in a 3D database using the 3D points cloud reconstruction, to identify the object, the 3D match search comprising a comparison of the reconstructed 3D points cloud of the object with 3D points clouds of known objects stored in the 3D database.

A system for modeling a three-dimensional structure utilizing two-dimensional segments comprising a memory and a processor in communication with the memory. The processor extracts a plurality of two-dimensional segments corresponding to the three-dimensional structure from a plurality of images indicative of different views of the three-dimensional structure. The processor determines a plurality of three-dimensional candidate segments based on the extracted plurality of two-dimensional segments and adds the plurality of three-dimensional candidate segments to a three-dimensional segment cloud. The processor transforms the three-dimensional segment cloud into a wireframe indicative of the three-dimensional structure by performing a wireframe extraction process on the three-dimensional segment cloud.

An object recognition system includes: an image capture system for capturing at least one image of an object, and for providing image data representative of the captured image; a patch identification system in communication with the image capture system for receiving the image data, and for identifying at least one image patch associated with the captured image, each image patch being associated with a potential grasp location on the object, each potential grasp location being described as an area that may be associated with a contact portion of an end effector of a programmable motion device; a feature identification system for capturing at least one feature of each image patch, for accessing feature image data in the database and for providing feature identification data responsive to the image feature comparison data; and an object identification system for providing object identify data responsive to the image feature comparison data.

One variation of the method for distributing censored videos of manufacturing procedures performed within a facility includes: accessing a video feed captured by a local device interfacing with a local operator during performance of a procedure within the facility; interpreting a set of objects depicted in the video feed based on features extracted from the video feed; accessing a minimum censorship specification for the procedure, the minimum censorship specification defining a set of object types corresponding to a first degree of censorship; identifying a subset of objects, in the set of objects, depicted in the video feed related to the procedure based on the set of object types defined in the minimum censorship specification; fogging the subset of objects in the video feed to generate a censored video feed; and serving the censored video feed to a remote viewer portal accessed by a remote viewer.

The present subject matter discloses an action recognition method, apparatus and device, a storage medium, and a computer program product, belonging to the field of image recognition. Multiple video frames in a target video are obtained. Feature extraction is performed on the multiple video frames respectively according to multiple dimensions to obtain multiple multi-channel feature patterns. Each video frame corresponds to one multi-channel feature pattern. Each channel represents one dimension. An attention weight of each multi-channel feature pattern is determined based on a similarity between every two multi-channel feature patterns. The attention weight is used for representing a degree of correlation between a corresponding multi-channel feature pattern and an action performed by an object in the target video. A type of the action is determined based on the multiple multi-channel feature patterns and the determined multiple attention weights.

A method is disclosed. For example, the method includes applying a clear coat layer on a substrate, drying the clear coat layer to form random microstructures in the clear coat layer, dispensing a printing fluid to print a graphical pattern on the clear coat layer, and generating a physical unclonable function (PUF) pattern by drying the printing fluid that fills the random microstructures formed in the clear coat layer.