A system and method for estimating dimensions of an approximately cuboidal object from a 3D image of the object acquired by an image sensor of the vision system processor is provided. An identification module, associated with the vision system processor, automatically identifies a 3D region in the 3D image that contains the cuboidal object. A selection module, associated with the vision system processor, automatically selects 3D image data from the 3D image that corresponds to approximate faces or boundaries of the cuboidal object. An analysis module statistically analyzes, and generates statistics for, the selected 3D image data that correspond to approximate cuboidal object faces or boundaries. A refinement module chooses statistics that correspond to improved cuboidal dimensions from among cuboidal object length, width and height. The improved cuboidal dimensions are provided as dimensions for the object. A user interface displays a plurality of interface screens for setup and runtime operation.

Search points in a search space may be projected onto images from cameras imaging different parts of the search space. Subimages, corresponding to the projected search points, may be selected and processed to determine if a target object has been detected. Based on subimages in which target objects are detected, as well as orientation data from cameras capturing images from which the subimages were selected, positions of the target objects in the search space may be determined.

A method and a system for vision-based defect detection are proposed. The method includes the following steps. A test audio signal is outputted to a device-under-test (DUT), and a response signal of the DUT with respect to the test audio signal is received to generate a received audio signal. Signal processing is performed on the received audio signal to generate a spectrogram, and whether the DUT has an unacceptable defect with respect to the predefined auditory standard is determined through computer vision according to the spectrogram.

A vision system (10) for a motor vehicle includes a stereo imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, a disparity calculation block (17) adapted to calculate a stereo disparity of left/right images captured by the stereo imaging apparatus (11), and a processing device (14) adapted to perform image processing of images captured by the imaging apparatus (11). The vision system is adapted to perform time sharing of the disparity calculation block (17) between the stereo disparity calculation and calculation of a one-dimensional optical flow of captured images in a horizontal direction only.

Methods and apparatus for visualizing a surface covering on at least a portion of a surface in an image of a scene. The method comprises identifying, using at least one computer processor, a surface plane from the image of the scene, determining, for each pixel of a plurality of pixels corresponding to the surface plane, whether the pixel corresponds to at least a portion of the surface in the scene, and generating an updated image of the scene by overlaying on the surface plane, a visualization of a plurality of surface covering tiles on pixels along the surface plane determined to correspond to at least a portion of the surface in the scene.

A method for updating camera poses includes receiving a set of captured depth maps associated with a scene and detecting a first shape and a second shape present in the scene. The method also includes, for each of the first shape and the second shape, creating a 3D mesh, creating a virtual camera associated with the 3D mesh, and rendering a depth map associated with the virtual camera. The method further includes identifying a subset of the captured depth maps such that each captured depth map in the subset contains at least a portion of either the first shape or the second shape. The method additionally includes updating the physical camera poses by jointly solving for the physical camera poses by optimizing an alignment between the first depth map, the second depth map, and the subset of the set of captured depth maps.

Methods, apparatus, systems, and articles of manufacture are disclosed to warp images for video processing. An example device includes horizontal warper circuitry configured to access an input image, decimate a first set of pixels in the input image by row, and interpolate a second set of pixels in the input image by row to produce a horizontally warped image. The example device further includes vertical warper circuitry configured to access the horizontally warped image, decimate a first set of pixels in the horizontally warped image by column, and interpolate a second set of pixels in the horizontally warped image by column to produce an output image.

Methods and apparatus for visualizing a surface covering on at least a portion of a surface in an image of a scene. The method comprises identifying, using at least one computer processor, a surface plane from the image of the scene, determining, for each pixel of a plurality of pixels corresponding to the surface plane, whether the pixel corresponds to at least a portion of the surface in the scene, and generating an updated image of the scene by overlaying on the surface plane, a visualization of a plurality of surface covering tiles on pixels along the surface plane determined to correspond to at least a portion of the surface in the scene.

A method for forming a reconstructed 3D mesh includes receiving a set of captured depth maps associated with a scene, performing an initial camera pose alignment associated with the set of captured depth maps, and overlaying the set of captured depth maps in a reference frame. The method also includes detecting one or more shapes in the overlaid set of captured depth maps and updating the initial camera pose alignment to provide a shape-aware camera pose alignment. The method further includes performing shape-aware volumetric fusion and forming the reconstructed 3D mesh associated with the scene.

Systems, methods, and non-transitory computer-readable media can provide at least one frame of a content item to a saliency prediction model, the saliency prediction model being trained to identify salient points of interest that appear in content items. Information describing at least a first salient point of interest that appears in the at least one frame can be obtained from the saliency prediction model. The first salient point of interest can be predicted to be of interest to users accessing the content item. A view-based projection can be applied to a region corresponding to the first salient point of interest, wherein the view-based projection enhances a quality in which the region is presented.