Abstract: The invention generally relates to an industrial or geodetic surveying device having a tracking unit configured to receive over a tracking channel a tracking signal which is used to track a cooperative target. According to the invention, the surveying device comprises a camera to generate image data, wherein based on the additional knowledge about the position of the cooperative target in an image generated in the locked state, the visual appearance of the target carrier is learned and the result is stored in the form of a detector for use in a backup tracking mode.

Abstract: A video analysis apparatus is connected to an image capturing apparatus including a plurality of cameras, in which the video analysis apparatus, for a plurality of persons in images captured by the cameras, tracks at least one of the plurality of persons, detects a plurality of parts of the tracked person, and on the basis of information defining scores used to determine a best shot of each of the parts, computes a score for the part for each of frames of videos from security cameras, compares, for each of the parts, the scores for each part computed for each of the frames to determine a best shot of each of the parts, stores, for each of the parts, a feature value in association with the part, and compares the feature values of each of the parts of the plurality of persons to determine identity of the persons.

Abstract: The present invention discloses a method, a system and a computer program product for Contract management. The invention includes optical character recognition for extraction of data attributes from the contracts. The invention further provides AI engine configured for processing a contract creation request through a bot based on analysis of a set of parameters associated with the request.

Abstract: Described is a system for contrast and entropy-based perception adaption to optimize perception. The system is operable for receiving an input image of a scene with a camera system and detecting one or more objects (having perception data) in the input image. The perception data of the one or more objects is converted into probes, which are then converted into axioms using probabilistic signal temporal logic. The axioms are evaluated based on probe bounds. If the axioms are within the probe bounds, then results are provided; however, if the axioms are outside of the probe bounds, the system estimates optimal contrast bounds and entropy bounds as perception parameters. The contrast and entropy in the camera system are then adjusted based on the perception parameters.

Abstract: Described is a system to evaluate and reduce perception error in object detection and recognition. The system includes a perception module that receives perception data (of an object(s)) from an environment proximate a mobile platform. Perception probes are generated that describe one or more characteristics of the objects. The perception probes are converted into probabilistic signal temporal logic (PSTL)-based constraints that provide axioms having statistical analysis of the perception probes. The axioms are evaluated to classify the perception probes as valid or erroneous. Optimal perception parameters are generated by solving an optimization problem based on the axioms, which allows the system to adjust the perception module based on the optimal perception parameters.

Abstract: A system and method for human motion detection and tracking are disclosed. In one embodiment, a smart device having an optical sensing instrument monitors a stage. Memory is accessible to a processor and communicatively coupled to the optical sensing instrument. The system captures an image frame from the optical sensing instrument. The image frame is then converted into a designated image frame format, which is provided to a pose estimator. A two-dimensional dataset is received from the pose estimator. The system then converts, using inverse kinematics, the two-dimensional dataset into a three-dimensional dataset, which includes time-independent static joint positions, and then calculates, using the three-dimensional dataset, the position of each of the respective plurality of body parts in the image frame.

Abstract: A method includes receiving an input video stream and scaling the input video stream into two or more spatial layers. For each spatial layer, the method also includes generating a temporal layer prediction pattern by: obtaining a temporal base layer for a corresponding spatial layer; identifying, based on the temporal base layer, a plurality of temporal layers and a plurality of temporal time slots during a temporal period; and aligning the temporal base layer for the corresponding spatial layer with one of the temporal time slots during the temporal period. Each temporal time slot is associated with one of the temporal base layer or one of the plurality of temporal layers for the corresponding spatial layer. The temporal base layer for each corresponding spatial layer is aligned with a different temporal time slot than each other temporal base layer for each other corresponding spatial layer.

Abstract: The present disclosure relates to a string matching method, a string matching apparatus, a storage medium, and an electronic device. The method can include loading a first string and obtaining position information of a node element of an AC automaton in the first string and a node position relation of the node element on the AC automaton. The method can further include creating a skip list based on the position information and the node position relation, performing a depth-first traversal on the AC automaton, and obtaining a first matching result of a path between each target node and a parent node of the target node and the first string based on the skip list. Further, the method can include outputting a matching result of the first string and the preset matching rule based on the first matching result of each path included in the AC automaton and the first string.

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: The image processing apparatus that generates a virtual viewpoint image includes a generation unit. The generation unit generates a virtual viewpoint image in which in accordance with a virtual viewpoint specified by the virtual viewpoint information. The degree of transparency of a specific object at a position a specific distance apart from a position of a first virtual viewpoint in a virtual viewpoint image in accordance with the first virtual viewpoint corresponding to a first angle of view, which is generated by the generation unit, is higher than a degree of transparency of an object at a position the specific distance apart from a position of a second virtual viewpoint in a virtual viewpoint image in accordance with the second virtual viewpoint corresponding to a second angle of view larger than the first angle of view.

Abstract: An image processing apparatus includes side cameras attached to a side portion of a vehicle and configured to provide an image obtained by capturing the rear of the side portion including a vehicle body region; a fisheye camera attached to a rear portion of the vehicle and configured to provide an image including the rear of the vehicle captured at a wide angle of view; a narrow-angle camera attached to the rear portion of the vehicle and configured to provide an image including the rear of the vehicle captured at a narrow angle of view; and a synthesizing unit configured to synthesize the image of the fisheye camera and the image of the narrow-angle camera corresponding to the vehicle body region of the image of the side camera in the vehicle body region.

Abstract: Sequence-level parameters are generated for an image frame sequence including sequence-level indicators for indicating metadata types present for each image frame in the sequence of image frames. Frame-present parameters are generated for a specific image frame in the sequence including frame-present indicators corresponding to the metadata types as indicated in the sequence-level parameters. The frame-present indicators identify first metadata types for which metadata parameter values are to be encoded in a coded bitstream as metadata payloads. The image frame sequence, the sequence-level parameters, the frame-present parameters and the metadata payloads are encoded in the coded bitstream. A recipient device can generate, from the specific image frame based partly on the metadata parameter values determined for the first metadata types, a target display image for a target display.

Abstract: An interactive method of a smart watch includes the following steps: S1. acquiring a vibration signal of an accelerometer and a gyroscope of a smart watch based on a vibration signal transmitted by a human body; S2. identifying the vibration signal by using an anomaly detection algorithm; S3. pre-processing the vibration signal, and further classifying and identifying the vibration signal by using an improved algorithm of a k-nearest neighbor algorithm; S4. analyzing the user's feedback on the results and correcting them in time to maintain a stable identification accuracy. The present disclosure also discloses an interactive system, including a signal detection module, an identification and classification module, and a real-time feedback module. In the present disclosure, the human body part is regarded as a virtual screen based on the vibration signal transmitted by the human body.

Abstract: In an image processing apparatus, a vehicle speed obtainer obtains vehicle speed information indicative of a speed of a vehicle. A deactivation controller determines whether the speed of the vehicle represented by the vehicle speed information is equal to or lower than a speed-related deactivation threshold previously determined for a target device. The target device is a selected one of first and second imaging devices. The selected one of the first and second imaging devices has one of first and second angular fields of view smaller than the other of the first and second angular fields of view. The deactivation controller deactivates a capture operation of the target device upon determination that the speed of the vehicle represented by the vehicle speed information is equal to or lower than the speed-related deactivation threshold previously determined for the target device.

Abstract: The present disclosure addresses the technical problem of information loss while representing a physiological signal in the form of symbols and for recognizing patterns inside the signal. Thus making it difficult to retain or extract any relevant information which can be used to detect anomalies in the signal. A system and method for anomaly detection and discovering pattern in a signal using morphology aware symbolic representation has been provided. The system discovers pattern atoms based on the strictly increasing and strictly decreasing characteristics of the time series physiological signal, and generate symbolic representation in terms of these pattern atoms. Additionally the method possess more generalization capability in terms of granularity. This detects discord/abnormal phenomena with consistency.

Abstract: Disclosed are methods, apparatuses, and systems for encoding and decoding an image. The present invention provides an intra prediction unit receives an input image, removes high frequency ingredients by low pass filtering an encoded luma pixel value in the input image during intra prediction, and generates a prediction block by predicting a chroma pixel value by using a low pass filter (LPF) LM chroma mode for applying an LM chroma mode, which is an extended chroma mode technique for generating a prediction block by predicting the chroma pixel value by applying a correlation between color planes to the luma pixel value having removed therefrom the high frequency ingredients.

Abstract: Embodiments of the present provide a cross-camera obstacle tracking method, system and medium. The method includes: obtaining obstacle tracking results of images captured by at least two cameras, wherein each obstacle tracking result comprises results after identifying and tracking at least one obstacle in the image captured by each camera, and each obstacle is labeled with a local identifier for each camera; in response to a triggering condition of a main camera in the cameras to fusion of cross-camera obstacles being satisfied, establishing a mapping relation between local identifiers of the obstacles in the cameras and global identifiers according to the obstacle tracking result of each of the cameras; determining similarities of obstacles according to the obstacle tracking result of each of the cameras, and performing fusion of the global identifiers on the same obstacle according to the similarities; and obtaining final obstacle tracking results labeled with the global identifiers.

Abstract: A system for building, training and productionizing machine learning models is disclosed. A model training specification is received, and a plurality of sets of hyper-parameters is obtained. Sets of training data and hyper parameter sets are distributed to distributed training systems. Models are trained in parallel using different sets of training data. Models are trained using multiple sets of hyper parameters. A candidate hyper-parameter set is selected, based on a measure of estimated effectiveness of the trained predictive models, and a production predictive model is generated by training a predictive model using the selected candidate hyper-parameter set and the complete set of training data.

Abstract: A method for implementing artificial intelligence agents to perform machine learning tasks using predictive analytics to leverage ensemble policies for maximizing long-term returns includes obtaining a set of inputs including a set of ensemble policies and a meta-policy parameter, selecting an action for execution within the system environment using a meta-policy function determined based in part on the set of ensemble policies and the meta-policy function parameter, causing the artificial intelligence agent to execute the selected action within the system environment, and updating the meta-policy function parameter based on the execution of the selected action.

Abstract: In one implementation, a method of operating a lenticular display is performed by a device including a processor, non-transitory memory, an image sensor, and a lenticular display. The method includes displaying, via the lenticular display, first content at a horizontal angle of a first user and second content, different than the first content, at a horizontal angle of a second user. The method further includes displaying, via the lenticular display, the first content at a second horizontal angle of the first user and the second content at a second horizontal angle of the second user.