A 3D depth image acquiring method and apparatus, and an image acquisition device are provided. The method is applied to an image acquisition device comprising a VIS-NIR picture sensor and an infrared structured light projection component. The VIS-NIR picture sensor comprises a plurality of dot matrix units each having a blue light photosensitive component, a green light photosensitive component, a red light photosensitive component and an NIR photosensitive component distributed thereon. The method comprises: controlling the blue light photosensitive component, the green light photosensitive component, the red light photosensitive component, the NIR photosensitive component and the infrared structured light projection component to operate, to obtain an optimum NIR image and an optimum VIS image; and processing the optimum VIS image and a depth image which is obtained by performing calculation on the optimum NIR image using a 3D depth mode, to obtain a 3D depth image.

In one embodiment, a method includes accessing first image data generated by a first image sensor having a first filter array that has a first filter pattern. The first filter pattern includes a first filter type corresponding to a spectrum of interest and a second filter type. The method also includes accessing second image data generated by a second image sensor having a second filter array that has a second filter pattern different from the first filter pattern. The second filter pattern includes a number of second filter types, the number of second filter types and the number of first filter types have at least one filter type in common. The method also includes determining a correspondence between one or more first pixels of the first image data and one or more second pixels of the second image data.

Image sensors are provided. An image sensor includes a substrate that includes a pixel region, a first surface, and a second surface that is opposite the first surface. The image sensor includes first and second photogates that are on the first surface and are configured to generate electric charge responsive to incident light in the pixel region. Moreover, the image sensor includes first and second lenses that are on the second surface and are configured to pass the incident light toward the first and second photogates.

A method for generating a three-dimensional (3D) lane model, the method including calculating a free space indicating a driving-allowed area based on a driving image captured from a vehicle camera, generating a dominant plane indicating plane information of a road based on either or both of depth information of the free space and a depth map corresponding to a front of the vehicle, and generating a 3D short-distance road model based on the dominant plane.

Embodiments of the present invention create a three-dimensional virtual model by a user identifying a three-dimensional object, capturing a plurality of two-dimensional images of said object in succession, said plurality of images being captured from different orientations, recording said plurality of images on a storage medium, determining the relative change in position of said plurality of images by comparing two subsequent images, wherein the relative change is determined by a difference in color intensity values between the pixels of one image and another image, generating a plurality of arrays from the difference determined and generating a computer image from said plurality of arrays, wherein said computer image represents said three-dimensional object.

A method for automatic registration of 3D image data, captured by a 3D image capture system having an RGB camera and a depth camera, includes capturing 2D image data with the RGB camera at a first pose; capturing depth data with the depth camera at the first pose; performing an initial registration of the RGB camera to the depth camera; capturing 2D image data with the RGB camera at a second pose; capturing depth data at the second pose; and calculating an updated registration of the RGB camera to the depth camera.

An imaging apparatus includes a first camera, a second camera, a first imaging condition setting portion, and a second imaging condition setting portion. The first camera includes a color filter portion and a first light receiving portion receiving light transmitted through the color filter portion, and which captures a color imaged. The second camera includes a spectroscopic element to disperse light having a predetermined spectral wavelength from incident light and to change the spectral wavelength to four or more wavelengths, and a second light receiving portion to receive the light dispersed by the spectroscopic element and capture a spectroscopic image of each wavelength dispersed by the spectroscopic element; The first imaging condition setting portion sets a first imaging condition for the first camera. The second imaging condition setting portion sets a second imaging condition for the second camera based on the first imaging condition.

A wearable apparatus may include an image display; a content receiver; and a processor configured to process image data received through the content receiver to generate an image frame, and control the image display to display the image frame. The processor may be configured to compare a vertical pixel line of a left edge portion of the image frame with a vertical pixel line of a right edge portion of the image frame, and when it is determined that the image frame is a 360-degree Virtual Reality (VR) image, process the 360-degree VR image.

An electrically controlled spectacle includes a spectacle frame and optoelectronic lenses housed in the frame. The lenses include a left lens and a right lens, each of the optoelectrical lenses having a plurality of states, wherein the state of the left lens is independent of the state of the right lens. The electrically controlled spectacle also includes a control unit housed in the frame, the control unit being adapted to control the state of each of the lenses independently.

A temporally consistent belief propagation system includes a disparity map buffer that provides a disparity map of a previous time; a belief propagation unit that generates an energy function according to a first image of a present time, a second image of the present time, a first image of the previous time and the disparity map of the previous time; and a disparity generating unit that generates a disparity map of the present time according to the energy function.