Abstract: Methods and apparatus are provided for 6DoF inside-out tracking game control. In one novel aspect, a multi-processor architecture is used for VI-SLAM. In one embodiment, the apparatus obtains overlapping image frames and sensor inputs of an apparatus, wherein the sensor inputs comprise gyrometer data, accelerometer data and magnetometer data, splits computation work onto a plurality of vector processors to obtain six degree of freedom (6DoF) outputs of the apparatus based on a splitting algorithm, and performs a localization process to generate 6DoF estimations, and a mapping process to generate a cloud of three-dimensional points associated to the descriptors of the map. In one embodiment, the localization process and mapping process are configured to run sequentially. In another embodiment, the localization process and mapping process are configured to run in parallel.

Abstract: Methods and apparatus are provided for 6DoF inside-out tracking game control. In one novel aspect, a multi-processor architecture is used for VI-SLAM. In one embodiment, the apparatus obtains overlapping image frames and sensor inputs of an apparatus, wherein the sensor inputs comprise gyrometer data, accelerometer data and magnetometer data, splits computation work onto a plurality of vector processors to obtain six degree of freedom (6DoF) outputs of the apparatus based on a splitting algorithm, and performs a localization process to generate 6DoF estimations, and a mapping process to generate a cloud of three-dimensional points associated to the descriptors of the map. In one embodiment, the localization process and mapping process are configured to run sequentially. In another embodiment, the localization process and mapping process are configured to run in parallel.

Abstract: Methods and apparatus are provided for 6DoF inside-out tracking game control. In one novel aspect, a multi-processor architecture is used for VI-SLAM. In one embodiment, the apparatus obtains overlapping image frames and sensor inputs of an apparatus, wherein the sensor inputs comprise gyrometer data, accelerometer data and magnetometer data, splits computation work onto a plurality of vector processors to obtain six degree of freedom (6DoF) outputs of the apparatus based on a splitting algorithm, and performs a localization process to generate 6DoF estimations, and a mapping process to generate a cloud of three-dimensional points associated to the descriptors of the map. In one embodiment, the localization process and mapping process are configured to run sequentially. In another embodiment, the localization process and mapping process are configured to run in parallel.

Abstract: Methods and apparatus are provided for 6DoF inside-out tracking game control. In one novel aspect, a multi-processor architecture is used for VI-SLAM. In one embodiment, the apparatus obtains overlapping image frames and sensor inputs of an apparatus, wherein the sensor inputs comprise gyrometer data, accelerometer data and magnetometer data, splits computation work onto a plurality of vector processors to obtain six degree of freedom (6DoF) outputs of the apparatus based on a splitting algorithm, and performs a localization process to generate 6DoF estimations, and a mapping process to generate a cloud of three-dimensional points associated to the descriptors of the map. In one embodiment, the localization process and mapping process are configured to run sequentially. In another embodiment, the localization process and mapping process are configured to run in parallel.

Abstract: Methods and apparatus are provided for 6DoF inside-out tracking game control. In one novel aspect, a multi-processor architecture is used for VI-SLAM. In one embodiment, the apparatus obtains overlapping image frames and sensor inputs of an apparatus, wherein the sensor inputs comprise gyrometer data, accelerometer data and magnetometer data, splits computation work onto a plurality of vector processors to obtain six degree of freedom (6DoF) outputs of the apparatus based on a splitting algorithm, and performs a localization process to generate 6DoF estimations, and a mapping process to generate a cloud of three-dimensional points associated to the descriptors of the map. In one embodiment, the localization process and mapping process are configured to run sequentially. In another embodiment, the localization process and mapping process are configured to run in parallel.

Abstract: This method of calibration comprising the reconstruction of a 3D mapping of 3D landmarks of an environment on the basis of digital images of the environment captured by the computer-based vision system (10) during the movement of the craft (2) along a trajectory. It comprises the optimization of at least one 3D mapping corresponding to a first sequence of images by considering at least one extrinsic parameter and/or at least one intrinsic parameter and/or at least one parameter of poses and/or one parameter of 3D landmarks as constant and the optimization of at least one 3D mapping corresponding to a second sequence of images, longer than the first image sequence and including the first image sequence, by considering said at least one extrinsic parameter and/or said at least one intrinsic parameter and/or said at least one parameter of poses and/or said at least one parameter of 3D landmarks as variable so as to estimate it.

Abstract: This method of calibration comprising the reconstruction of a 3D mapping of 3D landmarks of an environment on the basis of digital images of the environment captured by the computer-based vision system (10) during the movement of the craft (2) along a trajectory. It comprises the optimization of at least one 3D mapping corresponding to a first sequence of images by considering at least one extrinsic parameter and/or at least one intrinsic parameter and/or at least one parameter of poses and/or one parameter of 3D landmarks as constant and the optimization of at least one 3D mapping corresponding to a second sequence of images, longer than the first image sequence and including the first image sequence, by considering said at least one extrinsic parameter and/or said at least one intrinsic parameter and/or said at least one parameter of poses and/or said at least one parameter of 3D landmarks as variable so as to estimate it.