Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.

Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.

Abstract: Systems and methods for animating an avatar are provided. An example method of animating an avatar includes at an electronic device having one or more processors and memory, receiving an audio input, receiving a video input including at least a portion of a user's face, wherein the video input is separate from the audio input, determining one or more movements of the user's face based on the received audio input and received video input, and generating, using a neural network separately trained with a set of audio training data and a set of video training data, a set of characteristics for controlling an avatar representing the one or more movements of the user's face.

Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.

Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.

Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.

Abstract: A technique for generating virtual models of plants in a field is described. Generally, this includes recording images of plants in-situ; generating point clouds from the images; generating skeleton segments from the point cloud; classifying a subset of skeleton segments as unique plant features using the images; and growing plant skeletons from skeleton segments classified as unique plant feature. The technique may be used to generate a virtual model of a single, real plant, a portion of a real plant field, and/or the entirety of the real plant field. The virtual model can be analyzed to determine or estimate a variety of individual plant or plant population parameters, which in turn can be used to identify potential treatments or thinning practices, or predict future values for yield, plant uniformity, or any other parameter can be determined from the projected results based on the virtual model.