In exemplary embodiments, methods and systems are provided that include or utilize one or more automotive equipped cameras and a processor. The one or more automotive equipped cameras are configured to be onboard a vehicle and to obtain camera images during operation of the vehicle, the camera images including a view of one or more wheels of the vehicle. The processor is coupled to the one or more cameras, and is configured to at least facilitate: processing the camera images; and determining one or more states of the one or more wheels, including an alignment thereof, a health thereof, or both, based on the processing of the camera images.

A relocation method and a mobile machine using the same are provided. The method includes: obtaining a global map and a current scan map of a target scene where a mobile machine is located, and generating a local sub-map based on the global map; obtaining a black boundary in the local sub-map, determining a length and a curve complexity of the black boundary, and determining a weight of the black boundary based on the length and the curve complexity of the black boundary; determining an estimated pose and a target black boundary based on the local sub-map and the current scan image, and obtaining a matching value between the current scan image and the local sub-map based on a weight of the target black boundary; and determining the estimated pose as a relocated pose of the mobile machine in response to the matching value being larger than a preset threshold.

An electronic device using a spatio-temporal self-similarity (STSS) and a method of operating the electronic device are disclosed. The electronic device may generate an STSS tensor including a spatial self-similarity map and spatial cross-similarity maps for each position of a video feature map corresponding to an input video based on a temporal offset and a spatial offset. STSS feature vectors may be generated from the STSS tensor by decreasing a dimension of the spatial offset and maintaining a dimension of the temporal offset for each position of the STSS tensor. An STSS feature map may be generated by integrating the dimension of the temporal offset for each position of the STSS feature vectors. An inference on the input video may be based on a result of adding the STSS feature map to the video feature map.

A device include on-board memory, an applications processor, a digital signal processor (DSP) cluster, a configurable accelerator framework (CAF), and a communication bus architecture. The communication bus communicatively couples the applications processor, the DSP cluster, and the CAF to the on-board memory. The CAF includes a reconfigurable stream switch and data volume sculpting circuitry, which has an input and an output coupled to the reconfigurable stream switch. The data volume sculpting circuitry receives a series of frames, each frame formed as a two dimensional (2D) data structure, and determines a first dimension and a second dimension of each frame of the series of frames. Based on the first and second dimensions, the data volume sculpting circuitry determines for each frame a position and a size of a region-of-interest to be extracted from the respective frame, and extracts from each frame, data in the frame that is within the region-of-interest.

An image matching method includes extracting, from a first image of an object, a landmark patch including a landmark point of the object; extracting, from a second image of the object, a target patch corresponding to the landmark patch; and determining a target point in the second image corresponding to the landmark point based on a matching between the landmark patch and the target patch.

An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

A disparity estimation device calculates, for each of first pixels of a first image and each of second pixels of a second image, a first census feature amount and a second census feature amount, calculates, for each of the first pixels, a first disparity value of the first pixel with integer accuracy, extracts, for each of the first pixels, reference pixels located in positions corresponding to the first disparity value and a near disparity value close to the first disparity value from the second pixels, calculates sub-pixel evaluation values based on the relationship between the pixel values of the first pixel and the neighboring pixel and the pixel values of each of the reference pixels and the neighboring pixel, and estimates a second disparity value of the first pixel with sub-pixel accuracy by equiangular fitting.

When searching for a registered image similar to a query image, an image processing apparatus estimates an area having a difference by comparing images determined to be similar if a plurality of similar images is found at the time of search of a similar image using an image feature amount in order to enhance search accuracy. Then, the image processing apparatus compares the query image with the plurality of images similar to the query image based on the difference area.

Disclosed are a method and apparatus for determining a given variation of a form used by a filled in instance of that type of form from amongst a number of form templates. The given instance is aligned to each of the variants or form templates. The result of the alignment includes a series of key points that did not match up well (bad key points). The bad key points are taken from the form templates. Then, a set of pixel patches from around each of the bad key points of the form templates are extracted. The pixel patches are individually compared to corresponding pixel patches of the instance. The comparison generates a match score. The form template having the greatest match score is the correct form template.

Provided are an image processing device and the like which implement personal privacy protection while suppressing a reduction in visibility for an image. The image processing device is provided with: a memory storing instructions; and one or more processors configured to execute the instructions to: detect a person region that is a region where a person appears in an image captured by a camera device; and perform, on the person region, privacy processing a strength of which differs according to a depth associated with coordinates of the person region or a predetermined index related to the depth.