Abstract:
Methods and apparatus to convert images for computer-vision systems are disclosed. An example computer-vision system includes an image converter (112) to convert a near infrared light first image (202) to form a visible light image (206), and to update a coefficient of the image converter (112) based on a difference (214), an object recognizer (102) to recognize an object (208) in the first visible light image (206), and an object recognition analyzer (210) to determine the difference (214) between the object (208) recognized in the first visible light image (206) and an object (212) associated with the near infrared light image (202).
Abstract:
Systems, apparatuses and methods may provide for technology that generates, by a full inference path of a neural network, a first detection result associated with one or more objects in a first video frame. The technology may also generate, by a partial inference path of the neural network, a second detection result based on the first detection result, wherein the second detection result corresponds to a second video frame that is subsequent to the first video frame.
Abstract:
Technologies for multi-scale object detection include a computing device including a multi-layer convolution network and a multi-scale region proposal network (RPN). The multi-layer convolution network generates a convolution map based on an input image. The multi-scale RPN includes multiple RPN layers, each with a different receptive field size. Each RPN layer generates region proposals based on the convolution map. The computing device may include a multi-scale object classifier that includes multiple region of interest (ROI) pooling layers and multiple associated fully connected (FC) layers. Each ROI pooling layer has a different output size, and each FC layer may be trained for an object scale based on the output size of the associated ROI pooling layer. Each ROI pooling layer may generate pooled ROIs based on the region proposals and each FC layer may generate object classification vectors based on the pooled ROIs. Other embodiments are described and claimed.
Abstract:
A mechanism is described for facilitating efficient free in-plane rotation landmark tracking of images on computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting a first frame having a first image and a second frame having a second image, where the second image is rotated to a position away from the first image. The method may further include assigning a first parameter line and a second parameter line to the second image based on landmark positions associated with the first and second images, detecting a rotation angle between the first parameter line and the second parameter line, and rotating the second image back and forth within a distance associated with the rotation angle to verify positions of the first and second images.
Abstract:
Examples of systems and methods for augmented facial animation are generally described herein. A method for mapping facial expressions to an alternative avatar expression may include capturing a series of images of a face, and detecting a sequence of facial expressions of the face from the series of images. The method may include determining an alternative avatar expression mapped to the sequence of facial expressions, and animating an avatar using the alternative avatar expression.
Abstract:
Apparatuses, methods and storage medium associated with creating an avatar video are disclosed herein. In embodiments, the apparatus may one or more facial expression engines, an animation-rendering engine, and a video generator. The one or more facial expression engines may be configured to receive video, voice and/or text inputs, and, in response, generate a plurality of animation messages having facial expression parameters that depict facial expressions for a plurality of avatars based at least in part on the video, voice and/or text inputs received. The animation-rendering engine may be configured to receive the one or more animation messages, and drive a plurality of avatar models, to animate and render the plurality of avatars with the facial expression depicted. The video generator may be configured to capture the animation and rendering of the plurality of avatars, to generate a video. Other embodiments may be described and/or claimed.
Abstract:
Techniques related to automatic target object selection from multiple tracked objects for imaging devices are discussed. Such techniques may include generating one or more object selection metrics such as accumulated distances from frame center, accumulated velocities, and trajectory comparisons of predicted to actual trajectories for tracked objects and selecting the target object based on the object selection metric or metrics.
Abstract:
Managing images in an image database is described, comprising: when a query image is input, performing a match to determine whether an image similar to the query image exists within the database by comparing the images stored in the database with the query image; and if the image similar to the query image is a recognized image, providing at least one image in an image group to which the recognized image belongs and information thereon as a result, and if the image similar to the query image is an unrecognized image, providing at least one image in an image group to which the unrecognized image belongs as a result. When at least one image of the image group including the image similar to the query image is a recognized image, information on the corresponding recognized image is assigned to the images in the image group and provided as a result.
Abstract:
Computer-readable storage media, computing devices and methods are discussed herein. In embodiments, a computing device may be configured to perform facial recognition based on gradient based feature extractions of images of faces. In embodiments, the computing device may be configured to determine directional matching patterns of the images from the gradient based feature extraction and may utilize these directional matching patterns in performing a facial recognition analysis of the images of faces. Other embodiments may be described and/or claimed.
Abstract:
Examples of systems and methods for augmented facial animation are generally described herein. A method for mapping facial expressions to an alternative avatar expression may include capturing a series of images of a face, and detecting a sequence of facial expressions of the face from the series of images. The method may include determining an alternative avatar expression mapped to the sequence of facial expressions, and animating an avatar using the alternative avatar expression.