An image processing apparatus includes an extractor and an object identifier. The extractor extracts a left feature quantity included in a left image of a stereo image and a right feature quantity included in a right image of the stereo image by executing a convolution calculation multiple times on the basis of the left and right images with securing horizontal symmetry between the left feature quantity and the right feature quantity, and executes, at the convolution calculation, a concatenation process of concatenating pixel values between the left feature quantity and the right feature quantity using a calculation process to secure the horizontal symmetry. The object identifier performs object identification of an object on the basis of the left feature quantity and the right feature quantity.

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.

A method for providing telepresence by employing avatars is provided. The method includes steps of: (a) a corresponding location searching part determining a location in a first space where an avatar Y′ corresponding to a human Y in a second space will be placed, if a change of a location of the human Y in the second space is detected from an initial state, by referring to (i) information on the first space and the second space and (ii) information on locations of the humans X and Y, and the avatar X′ in the first and the second spaces; and (b) an avatar motion creating part creating a motion of the avatar Y′ by referring to information on the determined location where the avatar Y′ will be placed.

Methods for vehicle data collection by image analysis are provided. An example method involves positioning a camera in a vehicle to be pointed toward a field of interest in the vehicle, capturing an image of the field of interest with the camera, identifying a region of interest in the image that is expected to convey vehicle information, and running an image processing model over the region of interest to extract vehicle information from the image.

Disclosed are a method and a system for enhancing sound and picture quality based on scene recognition, and a display. The method includes: recognizing a real scene reflected in a current screen of the display; calculating sound and picture quality enhancement parameters matching the real scene; and controlling the display to play sound and picture corresponding to the real scene according to best sound and picture quality corresponding to the sound and picture quality enhancement parameters.

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.

Using a read sensor to sense wrong-way driving. A method may include sensing, by a rear sensor of a vehicle, an environment of the vehicle to provide rear sensed information; processing the rear sensed information to provide at least one rear-sensed vehicle progress direction indications; generating or receiving at least one front-sensed vehicle progress direction indications; wherein the at least one front-sensed vehicle progress direction indications is generated by processing front-sensed information acquired during right-way progress; comparing at least one rear-sensed vehicle progress direction indications to the at least one front-sensed vehicle progress direction indications to determine whether the vehicle is wrong-way driving; and responding to the finding of the wrong-way driving.

An apparatus detects a plurality of areas from an overall image, determines on each of the plurality of areas whether the area is a candidate for an area including an object as a processing target based on a determination reference value (first determination processing), acquires a zoom-in image of the area determined to be the candidate for the area including the object in the first determination processing, and determines whether the acquired zoom-in image is an image of the object (second determination processing). The apparatus identifies an area, in the overall image, corresponding to the zoom-in image determined not to be the image of the object in the second determination processing, and performs control to update the determination reference value used in the first determination processing based on image information of the identified area in the overall image.

A neural network, trained for the task of deriving the attribution of image regions that significantly influence classification in a tool for pathology classification, comprising (i) a contracting branch, (ii) an attenuation module, (iii) an interconnected upsampling branch, and (iv) a final mapping module.

A system identifies strong features in conjugate digital images and correlates the conjugate digital images for an identification of candidate tie points using only portions of the conjugate digital images that include the strong features.