A method for recognising objects in a three-dimensional image, the method being implemented by a system and comprising the following steps: • receiving an image of a three-dimensional scene acquired using a 3D sensor, with the acquired image comprising a plurality of 3D points each being associated with a ray connecting the 3D point to the 3D sensor; • receiving a plurality of geometric models each associated with a class of objects; • determining a segmentation of the scene so as to produce a plurality of segments each corresponding to an element of the scene, with a segment being a group of 3D points representing a geometric coherence; • determining at least one candidate pose for each determined segment and each geometric model; • for each segment, each geometric model and each candidate pose: - embedding the geometric model in the scene according to the candidate pose; - determining at least one set of 3D points from among: a first set consisting of the intersection points between the embedded geometric model and the rays of the points of said segment, a second set consisting of the points of said segment whose rays do not intersect the embedded geometric model, a third set consisting of the intersection points between the embedded geometric model and the rays of the points of the scene apart from said segment, a fourth set consisting of the points of the scene apart from said segment whose rays do not intersect the embedded geometric model; - computing a matching score between the embedded geometric model and said segment, as a function of at least one matching criterion selected from among: a proximity criterion between the first set and said segment, a distancing criterion between the second set and the embedded geometric model, a distancing criterion between the third set and said segment, a proximity criterion between the fourth set and the points of the scene apart from said segment; • determining an optimal score from among the set of computed scores; • selecting the geometric model and the candidate pose corresponding to the optimal score. • receiving an image of a three-dimensional scene acquired using a 3D sensor, with the acquired image comprising a plurality of 3D points each being associated with a ray connecting the 3D point to the 3D sensor; • receiving a plurality of geometric models each associated with a class of objects; • determining a segmentation of the scene so as to produce a plurality of segments each corresponding to an element of the scene, with a segment being a group of 3D points representing a geometric coherence; • determining at least one candidate pose for each determined segment and each geometric model; • for each segment, each geometric model and each candidate pose: - embedding the geometric model in the scene according to the candidate pose; - determining at least one set of 3D points from among: a first set consisting of the intersection points between the embedded geometric model and the rays of the points of said segment, a second set consisting of the points of said segment whose rays do not intersect the embedded geometric model, a third set consisting of the intersection points between the embedded geometric model and the rays of the points of the scene apart from said segment, a fourth set consisting of the points of the scene apart from said segment whose rays do not intersect the embedded geometric model; - computing a matching score between the embedded geometric model and said segment, as a function of at least one matching criterion selected from among: a proximity criterion between the first set and said segment, a distancing criterion between the second set and the embedded geometric model, a distancing criterion between the third set and said segment, a proximity criterion between the fourth set and the points of the scene apart from said segment; - embedding the geometric model in the scene according to the candidate pose; - determining at least one set of 3D points from among: a first set consisting of the intersection points between the embedded geometric model and the rays of the points of said segment, a second set consisting of the points of said segment whose rays do not intersect the embedded geometric model, a third set consisting of the intersection points between the embedded geometric model and the rays of the points of the scene apart from said segment, a fourth set consisting of the points of the scene apart from said segment whose rays do not intersect the embedded geometric model; - computing a matching score between the embedded geometric model and said segment, as a function of at least one matching criterion selected from among: a proximity criterion between the first set and said segment, a distancing criterion between the second set and the embedded geometric model, a distancing criterion between the third set and said segment, a proximity criterion between the fourth set and the points of the scene apart from said segment; • determining an optimal score from among the set of computed scores; • selecting the geometric model and the candidate pose corresponding to the optimal score.