Abstract: An efficient K-nearest neighbor search algorithm for three-dimensional (3D) lidar point cloud in unmanned driving and a use of the foregoing K-nearest neighbor search algorithm in a point cloud map matching process in the unmanned driving are provided. A novel data structure for fast K-nearest neighbor search is used, such that each voxel or sub-voxel includes a proper quantity of points to reduce redundant search. The novel K-nearest neighbor search algorithm is based on a double segmentation voxel structure (DSVS) and a field programmable gate array (FPGA). By means of the novel K-nearest neighbor search algorithm, nearest neighbors are searched for only in a neighboring expected area near a search point, thereby reducing search of redundant points. In addition, an optimized data transmission and access policy is used, which makes the algorithm more fit the characteristic of the FPGA.

Abstract: A method for generating a synthesized medical image by receiving a normal image includes generating first data based on a random selection, generating second data, and, based at least in part on the first and second data, modifying the normal image to form the synthesized medical image. Modifying the normal image comprises combining the first data and the second data. The first data characterizes an image that represents a lesion and the second data characterizes a transformation of that image as well as a location of the lesion.

Abstract: There is provided a method and a system configured to obtain an image of a one or more first areas of a semiconductor specimen acquired by an examination tool, determine data Datt informative of defectivity in the one or more first areas, determine one or more second areas of the semiconductor specimen for which presence of a defect is suspected based at least on an evolution of Datt, or of data correlated to Datt, in the one or more first areas, and select the one or more second areas for inspection by the examination tool.

Abstract: Methods for detecting areas of localized tilt on a sample using imaging reflectometry measurements include obtaining a first image without blocking any light reflected from the sample and obtaining a second image while blocking some light reflected from the sample at the aperture plane. The areas of localized tilt are detected by comparing first reflectance intensity values of pixels in the first image with second reflectance intensity values of corresponding pixels in the second image.

Abstract: In some implementations at an electronic device, training a dual EDNN includes defining a data structure of attributes corresponding to defined parts of a task, processing a first instance of an input using a first EDNN to produce a first output while encoding a first set of the attributes in a first latent space, and processing a second instance of the input using a second EDNN to produce a second output while encoding attribute differences from attribute averages in a second latent space. The device then determines a second set of the attributes based on the attribute differences and the attribute averages. The device then adjusts parameters of the first and second EDNNs based on comparing the first instance of the input to the first output, the second instance of the input to the second output, and the first set of attributes to the second set of attributes.

Abstract: Presented herein are systems and methods that provide for improved 3D segmentation of nuclear medicine images using an artificial intelligence-based deep learning approach. For example, in certain embodiments, the machine learning module receives both an anatomical image (e.g., a CT image) and a functional image (e.g., a PET or SPECT image) as input, and generates, as output, a segmentation mask that identifies one or more particular target tissue regions of interest. The two images are interpreted by the machine learning module as separate channels representative of the same volume. Following segmentation, additional analysis can be performed (e.g., hotspot detection/risk assessment within the identified region of interest).

Abstract: A method of operating a procedural language and content generation system that involves correlating environment objects and object movement to input controls through operation of a correlator, operating an interpreter to evaluate the correlation of the input controls and object/object movement against known libraries to generate programmatic instructions, storing the programmatic instructions as an instruction set, transforming the instruction set into executable commands through a compiler, and configuring control logic to perform the executable commands in response to receiving detected environment objects and detected object movement from an image processor.

Abstract: Exemplary embodiments are directed to a system of enhancing biometric analysis matching. A processing device is configured to analyze the probe short-range and broadband iris texture information of a probe image for iris biometric authenticity, and based on the biometric authenticity of the probe short-range iris texture information and the probe broadband iris texture information, determine the biometric authenticity of the subject. Exemplary embodiments are also directed to a system of enhancing biometric analysis matching efficiency. The processing device generates an optimized order of enrollment iris biometric data includes a listing of the enrollment iris biometric data ordered by closest match to furthest match between the probe and enrollment broadband iris texture information. The processing device analyzes the iris biometric data for biometric authenticity starting with the closest match between the probe and enrollment broadband iris texture information.

Abstract: Methods and apparatus are provided for determining quantization parameter predictors from a plurality of neighboring quantization parameters. An apparatus includes an encoder for encoding image data for at least a portion of a picture using a quantization parameter predictor for a current quantization parameter to be applied to the image data. The quantization parameter predictor is determined using multiple quantization parameters from previously coded neighboring portions. A difference between the current quantization parameter and the quantization parameter predictor is encoded for signaling to a corresponding decoder.

Abstract: This application discloses a map element extraction method and apparatus, and a server. The map element extraction method includes obtaining a laser point cloud and an image of a target scene, the target scene including a map element; performing registration between the laser point cloud and the image to obtain a depth map of the image; performing image segmentation on the depth map of the image to obtain a segmented image of the map element in the depth map; and converting a two-dimensional location of the segmented image in the depth map to a three-dimensional location of the map element in the target scene according to a registration relationship between the laser point cloud and the image.

Abstract: In a driving assistance device, a human body specifying unit acquires, as human body information, an image of a human body existing around a host vehicle in image data acquired by a camera. A quasi-skeleton estimation unit estimates a quasi-skeleton of the human body from the human body information. The radar or the LiDAR measures a distance to a part of the human body that corresponds to the quasi-skeleton.

Abstract: A device, system and method for controlling a communication device to provide notifications of successful documentation of events is provided. The device receives a type of a recognized event occurring at a location of an edge device. The device determines, based on the type of the recognized event, one or more multimedia data types for collection to document the recognized event. The device causes the edge device to collect multimedia data of the one or more multimedia data types. The device receives an indication that the multimedia data has been stored successfully. The device determines whether the multimedia data has successfully documented the recognized event. When the multimedia data has successfully documented the recognized event, the device controls the edge device to provide a notification of successful documentation of the recognized event.

Abstract: A commodity management device includes a camera interface circuit connectable to a camera to capture an image of one of commodities arranged in a row along a first direction from a back plate to a front of the shelf. The device includes a sensor interface circuit connectable to a sensor measuring a distance to the commodities in the row. A processor is configured to detect a change in the distance measured by the sensor, identify the commodities based on the image, then acquire a thickness of each commodity in the row, and calculate the number of the commodities removed from the shelf based on the distance change and the thickness of the commodities.

Abstract: An encoder system may include an analyzer that analyzes a current image area in an input video to select a transform. A selectable residue transformer, controlled by the analyzer, may perform the selectable transform on a residue image generated from the current image area and a predicted current image area, to generate a transformed residue image. An encoder may encode the transformed residue image to generate output data. The analyzer controls the encoder to encode information to identify the selectable transform and to indicate that the selectable transform for the current image area is different from a transform of a previous image area of the input video. A decoder system may include components appropriate for decoding the output data from the encoder system.

Abstract: A transfer system includes a first imaging and detection system that detects an object by using a captured first image, an industrial machine that operates by using information detected by the first imaging and detection system, a second imaging and detection system disposed upstream of the first imaging and detection system to detect an object by using a captured second image, and an operation terminal that outputs, to the second imaging and detection system, an instruction instructing that detection be performed, and to change imaging and detection system data used in the second imaging and detection system. The first imaging and detection system includes a receiving unit to receive the imaging and detection system data from the second imaging and detection system. The second imaging and detection system includes a transmitting unit to transmit the imaging and detection system data to the first imaging and detection system.

Abstract: An encoder system may include an analyzer that analyzes a current image area in an input video to select a transform. A selectable residue transformer, controlled by the analyzer, may perform the selectable transform on a residue image generated from the current image area and a predicted current image area, to generate a transformed residue image. An encoder may encode the transformed residue image to generate output data. The analyzer controls the encoder to encode information to identify the selectable transform and to indicate that the selectable transform for the current image area is different from a transform of a previous image area of the input video. A decoder system may include components appropriate for decoding the output data from the encoder system.

Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: A computer vision-based fastener loosening detection approach is described. A first image is captured at a first time and a second image is captured at a second time. A feature-based image registration is performed to create a third image. An intensity-based image registration is performed to create a fourth image. Registration errors are determined based on a comparison of the first and fourth images. A feature enhancement process is performed on the registration errors to determine whether the fastener has loosened between the first time and the second time.

Abstract: Embodiments relate to a method for real-time facial animation, and a processing device for real-time facial animation. The method includes providing a dynamic expression model, receiving tracking data corresponding to a facial expression of a user, estimating tracking parameters based on the dynamic expression model and the tracking data, and refining the dynamic expression model based on the tracking data and estimated tracking parameters. The method may further include generating a graphical representation corresponding to the facial expression of the user based on the tracking parameters. Embodiments pertain to a real-time facial animation system.