Abstract: A method of determining a triplet of parameters defining a ground plane based on a depth image includes determining a plurality of triplets of parameters, each defining a ground plane, spatial filtering of the parameters, and temporal filtering of the parameters. The temporal filtering is dependent on an indicator of quality of depth image data available for determination of the ground plane. The temporal filtering is dependent on an indicator of quality of the ground plane determined after spatial filtering. Similarly, the spatial filtering can be parameterized as a function of the two indicators. Globally, the more the estimated plane for a depth image can “explain” the points in this image, the more accurately planes of the subsequent images are determined. For the spatial filtering, the ground plane is searched in a more limited space, and, for the temporal filtering, the previously estimated ground planes considered to a lesser degree.

Abstract: A method for detection of a target present on at least two images of the same scene captured by separate cameras comprises a prior step for learning about targets under setup conditions and further comprises, under conditions of use, a simultaneous classification step for objects present on the images, the target being said to be detected as soon as an object is classified as being one of the targets learned during the learning step. The classification step includes a step for adapting at least one of the images to the setup conditions under which the learning step took place. Application: surveillance, assistance and safety based on stereoscopic images.

Abstract: A method for the detection of a target present in at least two images of the same scene acquired simultaneously by different cameras comprises, under development conditions, a prior target-learning step, said learning step including a step of modeling of the data X corresponding to an area of interest in the images by a distribution law P such that P(X)=P(X2d,X3d,XT)=P(X2d)P(X3d)P(XT) where X2d are the luminance data in the area of interest, X3d are the depth data in the area of interest, and XT are the movement data in the area of interest. The method also comprises, under operating conditions, a simultaneous step of classification of objects present in the images, the target being regarded as detected when an object is classified as being one of the targets learnt during the learning step. Application: monitoring, assistance and security on the basis of stereoscopic images.

Abstract: A method of determining a triplet of parameters defining a ground plane based on a depth image includes determining a plurality of triplets of parameters, each defining a ground plane, spatial filtering of the parameters, and temporal filtering of the parameters. The temporal filtering is dependent on an indicator of quality of depth image data available for determination of the ground plane. The temporal filtering is dependent on an indicator of quality of the ground plane determined after spatial filtering. Similarly, the spatial filtering can be parameterized as a function of the two indicators. Globally, the more the estimated plane for a depth image can “explain” the points in this image, the more accurately planes of the subsequent images are determined. For the spatial filtering, the ground plane is searched in a more limited space, and, for the temporal filtering, the previously estimated ground planes considered to a lesser degree.

Abstract: A method for the detection of a target present in at least two images of the same scene acquired simultaneously by different cameras comprises, under development conditions, a prior target-learning step, said learning step including a step of modeling of the data X corresponding to an area of interest in the images by a distribution law P such that P(X)=P(X2d,X3d,XT)=P(X2d)P(X3d)P(XT) where X2d are the luminance data in the area of interest, X3d are the depth data in the area of interest, and XT are the movement data in the area of interest. The method also comprises, under operating conditions, a simultaneous step of classification of objects present in the images, the target being regarded as detected when an object is classified as being one of the targets learnt during the learning step. Application: monitoring, assistance and security on the basis of stereoscopic images.

Abstract: A method for detection of a target present on at least two images of the same scene captured by separate cameras comprises a prior step for learning about targets under setup conditions and further comprises, under conditions of use, a simultaneous classification step for objects present on the images, the target being said to be detected as soon as an object is classified as being one of the targets learned during the learning step. The classification step includes a step for adapting at least one of the images to the setup conditions under which the learning step took place. Application: surveillance, assistance and safety based on stereoscopic images.