The present invention relates to a method for assisting in the detection of elements in an environment, comprising: the acquisition of a first wide-field image of an environment by a first sensor (14A) having a first field of view and a first resolution, the generation of a fused image from first narrow-field images of the environment acquired by a second sensor (14B) having a second field of view strictly less than the first field of view and a second resolution finer than the first resolution, In response to the detection of a difference relating to an element on a second wide-field image acquired by the first sensor (14A), compared to the first wide-field image, the acquisition of a second narrow-field image imaging the difference, and the update the fused image with the second narrow-field image.

An automatic forensic facial comparison system, FFC, having a questioned image (I1) and a reference image (I2), captured by means of acquisition of images of a subject, comprising processing means configured to carry out FFC steps: at least one morphological analysis stage (11), mandatory, and optionally a holistic comparison stage (12), and/or an image overlay stage (13), and/or a photo-anthropometry stage (14), and/or a decision-making stage (15). For each stage (11, 12, 13, 14) corresponding to FFC methods, the processing means calculate an overall indicator value of the stage carried out. In the last decision-making stage (15), the processing means calculate a fuzzy value by applying soft computing, obtained as a sum of the overall indicator value of each stage previously carried out (11, 12, 13, 14), each value being weighted by a weight based on a set of data to support the decision-making stage (15) indicative of a degree of reliability of each stage and of the quality of the starting images (I1, I2).

Described herein are computer-implemented systems and methods of creating a labeled image. The computer-implemented systems or methods may comprise tiling an input image comprising a native resolution and a native size to generate a set of tiled images and tiling instructions or an encoding thereof used to generate the set of tile images, labeling the set of tiled images to generate a set of labeled tile images, merging the set of labeled tile images using the tiling instructions or encoding thereof to generate a labeled merged image, wherein the labeled merged image comprises the native resolution, the native size, and one or more merged labels.

A method for estimating a pose of a deformable object includes: receiving, by a processor, a plurality of images depicting the deformable object from multiple viewpoints; computing, by the processor, one or more object-level correspondences and a class of the deformable object depicted in the images; loading, by the processor, a 3-D model corresponding to the class of the deformable object; aligning, by the processor, the 3-D model to the deformable object depicted in the plurality of images to compute a six-degree of freedom (6-DoF) pose of the object; and outputting, by the processor, the 3-D model and the 6-DoF pose of the object.

An item recognition system uses a top camera and one or more peripheral cameras to identify items. The item recognition system may use image embeddings generated based on images captured by the cameras to generate a concatenated embedding that describes an item depicted in the image. The item recognition system may compare the concatenated embedding to reference embeddings to identify the item. Furthermore, the item recognition system may detect when items are overlapping in an image. For example, the item recognition system may apply an overlap detection model to a top image and a pixel-wise mask for the top image to detect whether an item is overlapping with another in the top image. The item recognition system notifies a user of the overlap if detected.

An image sensor module includes an image sensor configured to generate image data and memory including at least a memory bank storing the image data and a processor-in-memory (PIM) circuit, the PIM circuit including a plurality of processing elements. The memory is configured to read the image data from the memory bank; generate optical flow data and pattern density data using the plurality of processing elements, the optical flow data indicating time-sequential motion of at least one object included in the image data, and the pattern density data indicating a density of a pattern of the image data; and output the image data, the optical flow data, and the pattern density data.

In one aspect, a request to generate an automated tour based on a set of panoramic images is received. Each particular panoramic image is associated with geographic location information and linking information linking the particular panoramic image with one or more other panoramic images in the set. A starting panoramic image and a second panoramic image are determined based at least in part on the starting panoramic image and the linking information associated with the starting and second panoramic images. A first transition between the starting panoramic image and the second panoramic image is also determined based at least in part on the linking information for these panoramic images. Additional panoramic images as well as a second transition for between the additional panoramic images are also determined. The determined panoramic images and transitions are added to the tour according to an order of the tour.

An image or a video may include a spherical capture of a scene. A punchout of the image or the video may be generated by placement of a viewing window at a center of a two-dimensional plane onto which the image or the video is mapped. The punchout of the image or the video may provide a panoramic view of the scene.

A system for localization of a safe landing zone comprises at least one image-capture device onboard an aerial vehicle, and an onboard processor coupled to the image-capture device. The processor is operative to execute instructions to perform a method that comprises: receive, from the image-capture device, two or more overlapping images of a landscape underneath the aerial vehicle; generate, based on the overlapping images, a landing zone heatmap of the landscape; identify, based on the landing zone heatmap, one or more regions of the landscape having potential landing zones and obstacles; and determine a location of a safe landing zone using a distance transform of the one or more regions of the landscape. The location of the safe landing zone is in an area within one of the potential landing zones that is farthest from the obstacles. The location of the safe landing zone is then stored in a database.

Disclosed herein are a surface defect detection method and apparatus. The surface defect detection method is performed by the surface defect detection apparatus. The surface defect detection method includes: acquiring a photographed image of an inspection target object; and detecting a defect by using the acquired photographed image. Acquiring the photographed image includes radiating pattern light of a stripe pattern having a predetermined interval onto a surface of the inspection target object, and acquiring a photographed image by photographing reflected light reflected from the surface of the inspection target object.