Abstract: An impact reducing device applied to a door or window which is closing includes a depth-sensing camera, an impact reducing system, and an impact reducing unit. The depth-sensing camera captures images of a target constantly, and obtains Z depth information of the target. The impact reducing system determines whether the target is going to close according to the Z depth information and controls the impact reducing unit to provide a resistance such as a strong jet of air when the target is going to close, to reduce violent impacts.

Abstract: A method for adjusting a working state of an electronic device includes setting a predetermined value range of feature data of a user, and acquiring current feature data of the user from the camera device. The current feature data is compared to the predetermined value range of feature data. A working state of the electronic device is changed when the current feature data is out of the predetermined value range of feature data.

Abstract: An unmanned aerial vehicle (UAV) detecting method is executed and applied in an UAV. The method can include creating a sample features database for a user, and storing the sample features database in a storage device; shooting a plurality of scene images from every direction around the user; capturing a plurality of features of the object from the scene image; comparing the sample features of user with the features of the object, and storing a new feature of the object different from the sample feature of user in the storage device; determining whether a tagger is around the user, and sending an alarm signal to the user.

Abstract: In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

Abstract: In some implementations, a computer-implemented method may include: identifying one or more neighboring minutiae within a particular octant neighborhood for the octant feature vector for each minutia included in a list of minutiae associated with a search fingerprint; computing, for each minutia included in the list of minutiae, a direction difference between each minutia included in the list of minutiae, and each of the one or more neighboring minutiae identified for the octant feature vector for each minutia included in the list of minutiae; computing, for each minutia included in the list of minutiae, a minutia quality confidence; and computing a fingerprint quality confidence.

Abstract: An electronic device including a processing unit and a storage device receives digital images of a flight area of an unmanned aerial vehicle (UAV) captured by an image capturing device. Then, the processing unit determines a flight position of the UAV in the flight area based on the digital images, and controls the UAV to move from the flight position to a predetermined position. The processing unit receives a vehicle direction of the UAV from an electronic compass unit of the UAV, and adjusts the vehicle direction of the UAV based on a predetermined direction. The processing unit controls the UAV to perform a predetermined operation when the UAV reaches the predetermined position and the vehicle direction is the same as the predetermined direction.

Abstract: A method for adjusting a working state of an electronic device includes setting a predetermined value range of feature data of a user, and acquiring current feature data of the user from the camera device. The current feature data is compared to the predetermined value range of feature data. A working state of the electronic device is changed when the current feature data is out of the predetermined value range of feature data.

Abstract: In one aspect, methods that use a novel representation, referred to as an octant feature vector (OFV), are used for matching distorted fingerprints. For instance, a feature-based matcher for distorted fingerprint matching may use a two-step local and global matching scheme to compare a set of feature vectors that are derived from minutiae of a reference fingerprint and a search fingerprint. The relative geometric relationships between the reference minutia and nearest minutiae may be derived and encoded into a feature vector based on orientation difference. The OFV is invariant to the rigid transformations and is insensitive to nonlinear distortions since the relative geometric relationships are independent from the rigid transformation.

Abstract: In some implementations, a computer-implemented method may include: identifying one or more neighboring minutiae within a particular octant neighborhood for the octant feature vector for each minutia included in a list of minutiae associated with a search fingerprint; computing, for each minutia included in the list of minutiae, a direction difference between each minutia included in the list of minutiae, and each of the one or more neighboring minutiae identified for the octant feature vector for each minutia included in the list of minutiae; computing, for each minutia included in the list of minutiae, a minutia quality confidence; and computing a fingerprint quality confidence.

Abstract: In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

Abstract: A method for adjusting a working state of an electronic device includes setting a reasonable value range of feature data of a user, and acquiring current feature data of the user from the camera device. The current feature data is compared to the reasonable value range of feature data. A working state of the electronic device is changed when the current feature data is out of the reasonable value range of feature data.

Abstract: A control method for an unmanned aerial vehicle (UAV) is provided. The method includes: obtaining, from a depth-sensing camera, images of a surface below the unmanned aerial vehicle; obtaining, from a gyroscope, current pitch angle of the unmanned aerial vehicle; determining, at the unmanned aerial vehicle, a current altitude of the unmanned aerial vehicle based on the images and the current pitch angle; determining, at the unmanned aerial vehicle, whether the current altitude of the unmanned aerial vehicle is less than a predefined value; and controlling, at the unmanned aerial vehicle, a drive unit to rotate so as to cause the unmanned aerial vehicle to slow down in a balanced condition if the current altitude of the unmanned aerial vehicle is less than a predefined value.

Abstract: In some implementations, a computer-implemented method may include: identifying one or more neighboring minutiae within a particular octant neighborhood for the octant feature vector for each minutia included in a list of minutiae associated with a search fingerprint; computing, for each minutia included in the list of minutiae, a direction difference between each minutia included in the list of minutiae, and each of the one or more neighboring minutiae identified for the octant feature vector for each minutia included in the list of minutiae; computing, for each minutia included in the list of minutiae, a minutia quality confidence; and computing a fingerprint quality confidence.

Abstract: In one aspect, methods that use a novel representation, referred to as an octant feature vector (OFV), are used for matching distorted fingerprints. For instance, a feature-based matcher for distorted fingerprint matching may use a two-step local and global matching scheme to compare a set of feature vectors that are derived from minutiae of a reference fingerprint and a search fingerprint. The relative geometric relationships between the reference minutia and nearest minutiae may be derived and encoded into a feature vector based on orientation difference. The OFV is invariant to the rigid transformations and is insensitive to nonlinear distortions since the relative geometric relationships are independent from the rigid transformation.

Abstract: In some implementations, a method includes: receiving, from the camera, a sample image that includes a fingerprint and a mensuration reference device, where the sample image is associated with a resolution; identifying (i) a plurality of edge candidate groups within the sample image, and (ii) a set of regularity characteristics associated with each of the plurality of edge candidate groups; determining that the associated set of regularity characteristics indicates the mensuration reference device; identifying a ruler candidate group, from each of the plurality of edge candidate groups, based at least on determining that the associated set of regularity characteristics indicates the mensuration reference device; computing a scale associated with the sample image based at least on extracting a set of ruler marks from the identified ruler candidate group; and generating, based at least on the scale associated with the sample image, a scaled image.

Abstract: In some implementations, a computer-implemented method includes an iterative minutiae matching technique that initially groups mated minutiae within a list of all possible minutiae between a reference fingerprint and a search fingerprint, and then successively performs a geometric consistency check of the mated minutiae within the group. In some instances, the iterative matching technique enables improved identification of globally aligned mated minutiae within distorted regions, which may be used to subsequently improve the calculation of a similarity score between a reference fingerprint and a search fingerprint.

Abstract: In one aspect, methods that use a novel representation, referred to as an octant feature vector (OFV), are used for matching distorted fingerprints. For instance, a feature-based matcher for distorted fingerprint matching may use a two-step local and global matching scheme to compare a set of feature vectors that are derived from minutiae of a reference fingerprint and a search fingerprint. The relative geometric relationships between the reference minutia and nearest minutiae may be derived and encoded into a feature vector based on orientation difference. The OFV is invariant to the rigid transformations and is insensitive to nonlinear distortions since the relative geometric relationships are independent from the rigid transformation.

Abstract: In some implementations, a computer-implemented method includes: obtaining a captured image including, (i) a latent fingerprint to be captured, and (ii) a template, surrounding the latent fingerprint, that contains plurality of symbols; extracting, using an image processing technique, one or more characteristics for each of the plurality of symbols; calculating a resolution for the captured image based at least on the extracted one or more characteristics for each of the plurality of symbols; generating a reconstructed desired image, based at least on (i) the calculated resolution of the captured image, and (ii) the one or more extracted characteristics for each of the plurality of symbols; and providing the reconstructed desired image to a fingerprint identification system to perform a particular fingerprint operation.

Abstract: In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

Abstract: A fingerprint matching system for fingerprint matching using virtual minutiae includes a fingerprint scanning device, including (i) an interface to a fingerprint scanner, and (ii) a sensor associated with the fingerprint scanner, configured to identify a match between a search fingerprint representing a fingerprint of a subject and a reference fingerprint from among a plurality of reference fingerprints representing fingerprints of a plurality of historical subjects; a database containing the plurality of reference fingerprints representing fingerprints of the plurality of historical subjects; and a computing device in communication with said database and said fingerprint scanning device.