Apparatuses, systems, and methods are provided for alignment of a camera based on an image captured by the camera. The camera can, for example, be supported by a support structure to face towards an image alignment reference marker such that an image captured by the camera contains the marker. The camera can, for example, be rotatably aligned relative to the marker to an aligned position based on the captured image.

A method and corresponding system for reconstructing the surface geometry of a three-dimensional object is disclosed. The system comprises a cluster of heterogeneous sensors, including a two-dimensional high-resolution camera and a three-dimensional depth camera, and a turntable operable to rotate incrementally. In operation, the turntable is rotated to first and second positions and two-dimensional and three-dimensional data sets are obtained using the two-dimensional high-resolution camera and the three-dimensional depth camera. Corresponding features from the two-dimensional data sets are identified and used to identify the same corresponding features in the three-dimensional data sets. The three-dimensional corresponding features are used to calculate a three-dimensional homography, which is used to align the three-dimensional data sets. Following alignment, a three-dimensional mesh is generated from the aligned data sets.

Disclosed are methods, circuits, devices, systems and functionally associated computer executable code for image acquisition with depth estimation. According to some embodiments, there may be provided an imaging device including: (a) one or more imaging assemblies with at least one image sensor; (b) at least one structured light projector adapted to project onto a scene a multiresolution structured light pattern, which patterns includes multiresolution symbols or codes; and (3) image processing circuitry, dedicated or programmed onto a processor, adapted to identify multiresolution structured light symbols/codes within an acquired image of the scene.

Disclosed are methods, circuits, devices, systems and functionally associated computer executable code for image acquisition with depth estimation. According to some embodiments, there may be provided an imaging device including: (a) one or more imaging assemblies with at least one image sensor; (b) at least one structured light projector adapted to project onto a scene a multiresolution structured light pattern, which patterns includes multiresolution symbols or codes; and (3) image processing circuitry, dedicated or programmed onto a processor, adapted to identify multiresolution structured light symbols/codes within an acquired image of the scene.

A depth map generation unit 22 generates a depth map that generates the depth map from images obtained by picking up a subject at a plurality of viewpoint positions by an image pickup unit 21. On the basis of the depth map generated by the depth map generation unit 22, an alignment unit 23 aligns polarized images obtained by the image pickup unit 21 picking up the subject at the plurality of viewpoint positions through polarizing filters in different polarization directions at the different viewpoint positions. A polarization characteristic acquisition unit 24 acquires a polarization characteristic of the subject from a desired viewpoint position by using the polarized images aligned by the alignment unit 23 to obtain the high-precision polarization characteristic with little degradation in temporal resolution and spatial resolution. It becomes possible to acquire the polarization characteristic of the subject at the desired viewpoint position.

A vehicle-mounted stereo camera device that achieves high-precision distance detection is provided. The provided vehicle-mounted stereo camera device includes a left camera and right camera disposed on a vehicle via a holder to cause visual fields to overlap each other, a stereo processor that calculates a distance to a body outside the vehicle based on images captured by the left camera and right camera and on positions on the vehicle, first and second geomagnetic sensors respectively disposed near the left camera and right camera, and a third geomagnetic sensor disposed on the holder. The stereo processor compares a geomagnetic value detected by the first or second geomagnetic sensor with a geomagnetic value detected by the third geomagnetic sensor, detects a displacement amount of the left camera or right camera, and changes a cutout position in the image captured by the left camera or right camera based on the displacement amount.

A method and apparatus for photographing using a plurality of sensors in an electronic device are disclosed. The electronic device includes a plurality of output units comprising output circuitry configured to output an identification signal to an external object, a sensor configured to acquire an identification signal that is a reflection of the identification signal from an external object, and a processor. The processor is configured to determine a first state of the external object, based on the reflected identification signal, to designate the plurality of output units as a first subset and a second subset, based at least on the first state of the external object, and to differently control the first subset and the second subset to output the identification signal.

The present invention is generally directed to methods and systems of estimating visibility around a vehicle and automatically configuring one or more systems in response to the visibility level. The visibility level can be estimated by comparing two images of the vehicle's surroundings, each taken from a different perspective. Distance of objects in the images can be estimated based on the disparity between the two images, and the visibility level (e.g., a distance) can be estimated based on the farthest object that is visible in the images.

A method and system to determine the disparity associated with one or more textured regions of a plurality of images is presented. The method comprises the steps of breaking up the texture into its color primitives, further segmenting the textured object into any number of objects comprising such primitives, and then calculating a disparity of these objects. The textured objects emerge in the disparity domain, after having their disparity calculated. Accordingly, the method is further comprised of defining one or more textured regions in a first of a plurality of images, determining a corresponding one or more textured regions in a second of the plurality of images, segmenting the textured regions into their color primitives, and calculating a disparity between the first and second of the plurality of images in accordance with the segmented color primitives.

A 3D camera uses a modulated visible light source for depth imaging and includes a processor operable to perform time multiplexing between image detection and depth or time-of-flight (ToF) detection using the same photodetectors. The camera can alternate between the image detection mode and the ToF detection mode to produce a continuous stream of color and depth images that can be overlaid without the need for any post-processing software. The camera can also be configured to determine time-of-flight using analog integration modules, thereby minimizing the circuitry necessary for analog-to-digital conversions and ToF calculations in the digital domain.