Abstract: An apparatus is provided. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of an object. Furthermore, the apparatus includes a memory storage unit to store the raw data. The apparatus also includes a pre-processing engine to generate a coarse segmentation map and a joint heatmap from the raw data. The coarse segmentation map is to outline the object and the joint heatmap is to represent a point on the object. The apparatus further includes a neural network engine to receive the raw data, the coarse segmentation map, and the joint heatmap. The neural network engine is to generate a plurality of two-dimensional maps. Also, the apparatus includes a mesh creator engine to generate a three-dimensional mesh based on the plurality of two-dimensional maps.

Abstract: An apparatus is provided to generate mechanical index maps for mesh rigging. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of an object. The apparatus further includes a memory storage unit to store the raw data. In addition, the apparatus includes a pre-processing engine to generate a segmentation map from the raw data. The segmentation map is to outline the object. Furthermore, the apparatus includes a neural network engine to generate a mechanical heatmap for a predefined key-point connector based on the segmentation map. The mechanical heatmap includes a mechanical weight index of the predefined key-point connector for each pixel.

Abstract: An apparatus is provided. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of an object. Furthermore, the apparatus includes a memory storage unit to store the raw data. The apparatus also includes a pre-processing engine to generate a coarse segmentation map and a joint heatmap from the raw data. The coarse segmentation map is to outline the object and the joint heatmap is to represent a point on the object. The apparatus further includes a neural network engine to receive the raw data, the coarse segmentation map, and the joint heatmap. The neural network engine is to generate a plurality of two-dimensional maps. Also, the apparatus includes a mesh creator engine to generate a three-dimensional mesh based on the plurality of two-dimensional maps.

Abstract: An apparatus is provided. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a representation of an object. Furthermore, the apparatus includes a memory storage unit to store the raw data. The apparatus also includes a pre-processing engine to generate a coarse segmentation map and a joint heatmap from the raw data. The coarse segmentation map is to outline the object and the joint heatmap is to represent a point on the object. The apparatus further includes a neural network engine to receive the raw data, the coarse segmentation map, and the joint heatmap. The neural network engine is to generate a plurality of two-dimensional maps. Also, the apparatus includes a mesh creator engine to generate a three-dimensional mesh based on the plurality of two-dimensional maps.

Abstract: An apparatus and a method for detecting, classifying and tracking road users on frames of video data are provided. An object detection unit identifies an object in a frame of the video data. A pre-filtering unit determines whether the identifier associated to an object corresponds to another identifier associated to the same object in the same frame of the video data when the identifiers overlap. A tracking unit matches the identified object to a corresponding object in another frame of the video data, such that a path of the sequence of matched objects is tracked throughout the frames of the video data. A scenario unit determines a safety indicator that is a function of the risk indicators indicating interactions between road users.

Abstract: An apparatus and a method for detecting, classifying and tracking road users on frames of video data are provided. An object detection unit identifies an object in a frame of the video data. A pre-filtering unit determines whether the identifier associated to an object corresponds to another identifier associated to the same object in the same frame of the video data when the identifiers overlap. A tracking unit matches the identified object to a corresponding object in another frame of the video data, such that a path of the sequence of matched objects is tracked throughout the frames of the video data. A scenario unit determines a safety indicator that is a function of the risk indicators indicating interactions between road users.