Generally, the disclosed systems and methods implement improved detection of objects in three-dimensional (3D) space. More particularly, an improved 3D object detection system can exploit continuous fusion of multiple sensors and/or integrated geographic prior map data to enhance effectiveness and robustness of object detection in applications such as autonomous driving. In some implementations, geographic prior data (e.g., geometric ground and/or semantic road features) can be exploited to enhance three-dimensional object detection for autonomous vehicle applications. In some implementations, object detection systems and methods can be improved based on dynamic utilization of multiple sensor modalities. More particularly, an improved 3D object detection system can exploit both LIDAR systems and cameras to perform very accurate localization of objects within three-dimensional space relative to an autonomous vehicle. For example, multi-sensor fusion can be implemented via continuous convolutions to fuse image data samples and LIDAR feature maps at different levels of resolution.

The technology provides a sign detection and classification methodology. A unified pipeline approach incorporates generic sign detection with a robust parallel classification strategy. Sensor information such as camera imagery and lidar depth, intensity and height (elevation) information are applied to a sign detector module. This enables the system to detect the presence of a sign in a vehicle's externa environment. A modular classification approach is applied to the detected sign. This includes selective application of one or more trained machine learning classifiers, as well as a text and symbol detector. Annotations help to tie the classification information together and to address any conflicts with different the outputs from different classifiers. Identification of where the sign is in the vehicle's surrounding environment can provide contextual details. Identified signage can be associated with other objects in the vehicle's driving environment, which can be used to aid the vehicle in autonomous driving.

A system and method to identify and correlate identifying information or signatures with one or more targets of interest. The system may include a plurality of collection systems to capture information related to visual identifiers and/or electronic signatures associated with targets in selected locations. The system may further include an intelligence system to determine a target of interest based on the information related to visual identifiers and/or electronic signatures and to track the target of interest.

A hearing aid system for individual identification of a hearing aid system may include a wearable camera, a microphone, and at least one processor. The processor may be programmed to receive a plurality of images captured by the wearable camera; receive audio signals representative of sounds captured by the microphone; and identify a first audio signal, from among the received audio signals, representative of a voice of a first individual. The processor may transcribe and store, in a memory, text corresponding to speech associated with the voice of the first individual and determine whether the first individual is a recognized individual. If the first individual is a recognized individual, the processor may associate an identifier of the first recognized individual with the stored text corresponding to the speech associated with the voice of the first individual.

Techniques for estimating crop maturity using remote sensing imagery are disclosed. A method may include a step of providing a remote sensing image of crops acquired at an image acquisition time, for example, a synthetic aperture radar image acquired from a satellite. The method may also include a step of predicting a maturity level of the crops at the image acquisition time based on input crop maturity data from an input time and weather-based growth indication data from between the input time and the image acquisition time. The weather-based growth indication data may include growing degree day data. The method may further include a step of updating the predicted maturity level to an updated maturity level of the crops based on the remote sensing image and a response model relating remote sensing image information to crop maturity information. The predicting and updating steps may involve performing a particle filtering operation.

There is provided a computer implemented method for generating summary images from 3D medical images, comprising: receiving a 3D medical image, dividing the 3D medical images into a sequence of a plurality 2D images, computing a similarity dataset indicative of an amount of similarity between each pair of the plurality of 2D images, segmenting the similarity dataset into a plurality of slabs by minimizing the amount of similarity between consecutive slabs and maximizing the amount of similarity within each slab, aggregating, for each respective slab, the plurality of 2D images into a respective summary image, and presenting on a display, the respective summary image.

An information processing apparatus recognizes a target within an actual image by executing processing of a neural network. The information processing apparatus obtains intermediate outputs which correspond to the actual image and a computer graphics (CG) image and which are from a hidden layer when each of the actual image and the CG image has been separately input to the neural network, and causes the neural network to perform learning with use of an evaluation values based on a first evaluation function and a second evaluation function, the first evaluation function causing the evaluation value to decrease as a difference between a recognition result and training data decreases, the second evaluation function causing the evaluation value to decrease as a difference between the intermediate outputs corresponding to the actual image and the CG image decreases.

System, device, and method of Augmented Reality based mapping of a venue and navigation within a venue. A method includes: performing a crowd-sourced mapping process, that maps a retail store and maps particular products sold within that retail store, based on computer-vision analysis of a plurality of images captured by a plurality of end-user devices of customers within that retail store; and generating a representation of a store map reflecting actual real-time location of particular products within that retail store. Turn-by-turn walking directions are provided, to guide the user from his current in-store location towards a destination product within that retail store. Augmented Reality promotions, advertisements and marketing content elements, route guidance, and other content are generated and displayed on the end-user device.

A background scenery portion may be identified in each of a plurality of image sets of an object, where each image set includes images captured simultaneously from different cameras. A correspondence between the image sets may determined, where the correspondence tracks control points associated with the object and present in multiple images. A multi-view interactive digital media representation of the object that is navigable in one or more dimensions and that includes the image sets may be generated and stored.

Provided are a depth image processing method, and a small obstacle detection method and system. The method comprises calibration of sensors, distortion and epipolar rectification, data alignment, and sparse stereo matching. The depth image processing method and the small obstacle detection method and system of the present invention only requires execution of sparse stereo matching on hole portions of a structured light depth image, and do not requires stereo matching of the entire image, thereby significantly reducing the overall computation load for processing a depth image, and enhancing the robustness of a system.