Abstract: A method of recognizing animals includes recognizing a plurality of body parts of a plurality of animals based on at least one image of the animals, in which the plurality of body parts include a plurality of types of body parts, including determining first estimated positions of the recognized body parts in the at least one image. The method includes estimating a plurality of first associations of body parts based on the at least one image of the animals, each first association of body parts associates a body part of an animal with at least one other body part of the same animal, including determining relative positions of the body parts in each estimated first association of body parts in the at least one image.

Abstract: The invention relates to a computer-implemented method of tracking animals is provided. Such a method typically includes recognizing, by using at least one data processor, individual animals in images of a plurality of the animals; and tracking the animals using a probabilistic tracking-by-detection process. In another aspect, a system for recognizing animals is provided. Such a system typically includes an instance detection and part localization module; a visual marker classification module; a fixed-cardinality track interpolation module; and a maximum a posteriori estimation of animal identity module.

Abstract: A method of recognizing animals includes recognizing a plurality of body parts of a plurality of animals based on at least one image of the animals, in which the plurality of body parts include a plurality of types of body parts, including determining first estimated positions of the recognized body parts in the at least one image. The method includes estimating a plurality of first associations of body parts based on the at least one image of the animals, each first association of body parts associates a body part of an animal with at least one other body part of the same animal, including determining relative positions of the body parts in each estimated first association of body parts in the at least one image.

Abstract: A method of recognizing animals includes recognizing a plurality of body parts of a plurality of animals based on at least one image of the animals, in which the plurality of body parts include a plurality of types of body parts, including determining first estimated positions of the recognized body parts in the at least one image. The method includes estimating a plurality of first associations of body parts based on the at least one image of the animals, each first association of body parts associates a body part of an animal with at least one other body part of the same animal, including determining relative positions of the body parts in each estimated first association of body parts in the at least one image.

Abstract: A method of recognizing animals includes recognizing a plurality of body parts of a plurality of animals based on at least one image of the animals, in which the plurality of body parts include a plurality of types of body parts, including determining first estimated positions of the recognized body parts in the at least one image. The method includes estimating a plurality of first associations of body parts based on the at least one image of the animals, each first association of body parts associates a body part of an animal with at least one other body part of the same animal, including determining relative positions of the body parts in each estimated first association of body parts in the at least one image.

Abstract: Implementations directed to providing a computer-implemented method comprising receiving, from a motion sensing device, a plurality of image frames that includes information regarding a plurality of animals housed in a group-housed environment, determining a coordinate space of the group-housed environment based on an analysis of a first image frame of the image frames, generating, based on the analysis of the first image frame, an ellipsoid model for each animal based on defined surface points for each animal weighted according to a likely proximity to a crest of a spine of the respective animal, and tracking a position and an orientation of each animal within the image frames by enforcing shape consistency of the ellipsoid models, and adjusting the position of each of the ellipsoid models based on the defined surface points for each animal and a maximum likelihood formulation of a movement distance for each animal.

Abstract: Implementations directed to providing a computer-implemented method comprising receiving, from a motion sensing device, a plurality of image frames that includes information regarding a plurality of animals housed in a group-housed environment, determining a coordinate space of the group-housed environment based on an analysis of a first image frame of the image frames, generating, based on the analysis of the first image frame, an ellipsoid model for each animal based on defined surface points for each animal weighted according to a likely proximity to a crest of a spine of the respective animal, and tracking a position and an orientation of each animal within the image frames by enforcing shape consistency of the ellipsoid models, and adjusting the position of each of the ellipsoid models based on the defined surface points for each animal and a maximum likelihood formulation of a movement distance for each animal.