An object tracking system includes a first sensor, a second sensor, and a tracking system. The first sensor is configured to capture a first frame of a global plane for at least a first portion of a space. The second sensor is configured to capture a second frame of at least a second portion of the space. The tracking system is configured to determine the object is within an overlap region with the second sensor based on a first pixel location. The tracking system is further configured to determine a first coordinate in the global plane for the object, to determine a second pixel location in the second frame for the object based on the first coordinate, and to store the second pixel location with an object identifier a tracking list associated with the second sensor.

A method includes obtaining, using at least one processor of an electronic device, multiple calibration parameters associated with multiple sensors of a selected mobile device. The method also includes obtaining, using the at least one processor, an identification of multiple imaging tasks. The method further includes obtaining, using the at least one processor, multiple synthetically-generated scene images. In addition, the method includes generating, using the at least one processor, multiple training images and corresponding meta information based on the calibration parameters, the identification of the imaging tasks, and the scene images. The training images and corresponding meta information are generated concurrently, different ones of the training images correspond to different ones of the sensors, and different pieces of the meta information correspond to different ones of the imaging tasks.

An automobile-mounted imaging apparatus and a computer readable storage medium for detecting a distance to at least one object. The apparatus comprises circuitry configured to select at least two images from images captured by at least three cameras to use for detecting the distance to the at least one object based on at least one condition. Alternatively or additionally, the apparatus comprises circuitry configured to select two cameras of at least three cameras for detecting the distance to the at least one object based on at least one condition. Alternatively or additionally, the apparatus comprises circuitry configured to determine which of at least two cameras to use for detecting the distance to the at least one object based on at least one condition from at least three cameras capturing images.

Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itself—rather than using a priori definitions for what should constitute a measurable unit of action—identifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.

A capturing device has a lens block that includes a lens for focusing light from a subject during a daytime, the subject includes a vehicle. The capturing device further includes an image sensor that captures an image based on light from the subject focused by the lens, and a processor that generates a face image of an occupant riding in the vehicle based on a first number of captured imaged of the subject which are captured by the image sensor at different times. The processor generates the face image of the occupant further based on a second number of captured images in which a luminance value of a region of interest is equal to or smaller than a threshold value among the first number of captured images of the subject.

Systems and methods for optimizing sensory signal capturing by reconfiguring robotic device configurations. A method includes determining at least one predicted future sensor reading for a robotic device based on navigation path data of the robotic device, wherein the robotic device is deployed with at least one sensor, wherein each predicted future sensor reading is an expected value of a future sensory signal; determining an optimized sensor configuration based on the at least one predicted future sensor reading, wherein the optimized sensor configuration optimizes capturing of sensor signals by the at least one sensor; and reconfiguring the at least one sensor based on the optimized sensor configuration, wherein reconfiguring the at least one sensor further comprises modifying at least one sensor parameter of the at least one sensor based on the optimized sensor configuration.

A sensor arrangement may include a light sensor, a lens, and a filter. The lens may include a distal end positioned toward an environment and a proximal end that is opposite the distal end and positioned toward the light sensor. The filter may be situated between the light sensor and the proximal end of the lens. The filter may be configured to permit a preconfigured set of wavelengths of light from the environment to be sensed by the light sensor.

An illustrative method includes accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters. The method further includes generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters. The method further includes determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

In 2019, the World Health Organization stated that globally, approximately 2.2 billion people live with some form of vision impairment. Visual impairment limits the ability to perform everyday tasks and adversely affects the ability to interact with the surrounding world, thus discouraging individuals navigating unpredictable and unknown environments. The present invention is a method and a system to define and develop a smart navigation intelligent cane (i-Cane) that enables a visually impaired person to navigate his or her environment. The method and the system detects objects along the path of the visually impaired person, measures the distance of the objects from the person, identifies the objects, uses speech to alert the person of the approaching objects, the type of objects obstructing the path, and the distance between the objects and the person.

An image generation apparatus includes a processing circuit and a memory storing at least one computational image. The at least one computational image is a light-field image, a compressive sensing image, or a coded image. The processing circuit (a1) identifies a position of an object in the at least one computational image using a classification device, (a2) generates, using the at least one computational image, a display image in which an indication for highlighting the position of the object is superimposed, and (a3) outputs the display image.