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公开(公告)号：US11350039B2
公开(公告)日：2022-05-31
申请号：US17133345
申请日：2020-12-23
摘要： 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.
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公开(公告)号：US10583324B2
公开(公告)日：2020-03-10
申请号：US15943662
申请日：2018-04-02
摘要： Described is a system for prediction of adversary movements. In an aspect, the system includes one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of computing relative positions of multiple objects of interest, generating a feature representation by forming a matrix based on the relative positions, predicting movement of the multiple objects of interest by applying clustering to the feature representation and by performing canonical correlation analysis, and controlling a device based on the predicted movement of the multiple objects of interest.
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公开(公告)号：US20180290019A1
公开(公告)日：2018-10-11
申请号：US15943662
申请日：2018-04-02
摘要： Described is a system for prediction of adversary movements. In an aspect, the system includes one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of computing relative positions of multiple objects of interest, generating a feature representation by forming a matrix based on the relative positions, predicting movement of the multiple objects of interest by applying clustering to the feature representation and by performing canonical correlation analysis, and controlling a device based on the predicted movement of the multiple objects of interest.
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公开(公告)号：US11288498B2
公开(公告)日：2022-03-29
申请号：US16931420
申请日：2020-07-16
发明人： Amir M. Rahimi , Hyukseong Kwon , Heiko Hoffmann , Soheil Kolouri
摘要： Described is a system for learning actions for image-based action recognition in an autonomous vehicle. The system separates a set of labeled action image data from a source domain into components. The components are mapped onto a set of action patterns, thereby creating a dictionary of action patterns. For each action in the set of labeled action data, a mapping is learned from the action pattern representing the action onto a class label for the action. The system then maps a set of new unlabeled target action image data onto a shared embedding feature space in which action patterns can be discriminated. For each target action in the set of new unlabeled target action image data, a class label for the target action is identified. Based on the identified class label, the autonomous vehicle is caused to perform a vehicle maneuver corresponding to the identified class label.
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公开(公告)号：US20210227117A1
公开(公告)日：2021-07-22
申请号：US17133345
申请日：2020-12-23
摘要： 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.
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公开(公告)号：US20210089837A1
公开(公告)日：2021-03-25
申请号：US17030354
申请日：2020-09-23
摘要： 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.
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公开(公告)号：US10755424B2
公开(公告)日：2020-08-25
申请号：US15971982
申请日：2018-05-04
IPC分类号： G06K9/62 , G06T7/262 , G06T7/277 , G06N3/00 , G06N20/00 , G06K9/00 , A63B69/00 , G08G5/00 , G08G9/00 , A63B24/00
摘要： Described is a system for predicting multi-agent movements. A Radon Cumulative Distribution Transform (Radon-CDT) is applied to pairs of signature-formations representing agent movements. Canonical correlation analysis (CCA) components are identified for the pairs of signature-formations. Then, a relationship between the pairs of signature formations is learned using the CCA components. A counter signature-formation for a new dataset is predicted using the learned relationship and a new signature-formation. Control parameters of a device can be adjusted based on the predicted counter signature-formation.
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公开(公告)号：US20180293736A1
公开(公告)日：2018-10-11
申请号：US15949013
申请日：2018-04-09
IPC分类号： G06T7/20
摘要： Described is a system for implicitly predicting movement of an object. In an aspect, the system includes one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations of providing an image of a first trajectory to a predictive autoencoder, and using the predictive autoencoder, generating a predicted tactical response that comprises a second trajectory based on images of previous tactical responses that were used to train the predictive autoencoder, and controlling a device based on the predicted tactical response.
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公开(公告)号：US12073613B1
公开(公告)日：2024-08-27
申请号：US17743356
申请日：2022-05-12
发明人： Hyukseong Kwon , Alexie Pogue , Kevin Lee , Amir M. Rahimi , Amit Agarwal , Rajan Bhattacharyya
摘要： Described is a system for adapting to perception errors in object detection and recognition. The system receives, with a perception module, perception data from an environment proximate a mobile platform that reflects objects in the environment. Perception probes representing perception characteristics of object detections are generated from the perception data. Using the perception probes, spatial logic-based constraints and temporal logic-based constraints are generated. Spatial perception parameters are determined by solving an optimization problem using a set of the spatial logic-based constraints. Temporal perception parameters are determined by solving an optimization problem using a set of temporal logic-based constraints. The spatial perception parameters and the temporal perception parameters are combined to estimate a final perception parameter. The perception module is adjusted based on the final perception parameter.
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公开(公告)号：US11334767B2
公开(公告)日：2022-05-17
申请号：US17030354
申请日：2020-09-23
摘要： 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.
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