Abstract: A method and a system for calibrating an inertial measurement unit (IMU) via images of a calibration target are provided herein. The method may include: measuring parameters via an IMU; capturing a plurality of calibration images of a scene that contains at least one calibration target, wherein the calibration images are taken from different locations and/or orientations, wherein each of the calibration images shares a common calibration target with at least one other calibration image; calculating, based on the at least one common calibration target, a position and orientation of the sensing device relative to the calibration target, for each location of the capturing of the calibration images; and calibrating the IMU by comparing relative motion between two of the calibration images based on the calculated relative position and orientation, to measurements of the parameters taken by the IMU in time ranges corresponding to the at least two calibration images.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: Methods and systems for recalibrating sensing devices without using familiar targets are provided herein. The method may include: capturing a scene using a sensing device; determining whether or not the device is calibrated; in a case that said sensing device is calibrated, adding at least one new landmark to the known landmarks; in a case that said sensing device is not calibrated, determining at least some of the captured objects as objects stored on a database as known landmarks at the scene whose position is known; and calibrating the sensing device based on the known landmarks. The system may have various architectures that include a sensing device which captures images of the scene and further derive 3D data on the scene of some form.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: A method and a system for calibrating an inertial measurement unit (IMU) via images of a calibration target are provided herein. The method may include: measuring parameters via an IMU; capturing a plurality of calibration images of a scene that contains at least one calibration target, wherein the calibration images are taken from different locations and/or orientations, wherein each of the calibration images shares a common calibration target with at least one other calibration image; calculating, based on the at least one common calibration target, a position and orientation of the sensing device relative to the calibration target, for each location of the capturing of the calibration images; and calibrating the IMU by comparing relative motion between two of the calibration images based on the calculated relative position and orientation, to measurements of the parameters taken by the IMU in time ranges corresponding to the at least two calibration images.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: A method and a system for calibrating an inertial measurement unit (IMU) via images of a calibration target are provided herein. The method may include: measuring parameters via an IMU; capturing a plurality of calibration images of a scene that contains at least one calibration target, wherein the calibration images are taken from different locations and/or orientations, wherein each of the calibration images shares a common calibration target with at least one other calibration image; calculating, based on the at least one common calibration target, a position and orientation of the sensing device relative to the calibration target, for each location of the capturing of the calibration images; and calibrating the IMU by comparing relative motion between two of the calibration images based on the calculated relative position and orientation, to measurements of the parameters taken by the IMU in time ranges corresponding to the at least two calibration images.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: A method and a system for calibrating an inertial measurement unit (IMU) via images of a calibration target are provided herein. The method may include: measuring parameters via an IMU; capturing a plurality of calibration images of a scene that contains at least one calibration target, wherein the calibration images are taken from different locations and/or orientations, wherein each of the calibration images shares a common calibration target with at least one other calibration image; calculating, based on the at least one common calibration target, a position and orientation of the sensing device relative to the calibration target, for each location of the capturing of the calibration images; and calibrating the IMU by comparing relative motion between two of the calibration images based on the calculated relative position and orientation, to measurements of the parameters taken by the IMU in time ranges corresponding to the at least two calibration images.

Abstract: Methods and systems for recalibrating sensing devices without using familiar targets are provided herein. The method may include: capturing a scene using a sensing device; determining whether or not the device is calibrated; in a case that said sensing device is calibrated, adding at least one new landmark to the known landmarks; in a case that said sensing device is not calibrated, determining at least some of the captured objects as objects stored on a database as known landmarks at the scene whose position is known; and calibrating the sensing device based on the known landmarks. The system may have various architectures that include a sensing device which captures images of the scene and further derive 3D data on the scene of some form.

Abstract: Methods and systems for recalibrating sensing devices without using familiar targets are provided herein. The method may include: capturing a scene using a sensing device; determining whether or not the device is calibrated; in a case that said sensing device is calibrated, adding at least one new landmark to the known landmarks; in a case that said sensing device is not calibrated, determining at least some of the captured objects as objects stored on a database as known landmarks at the scene whose position is known; and calibrating the sensing device based on the known landmarks. The system may have various architectures that include a sensing device which captures images of the scene and further derive 3D data on the scene of some form.

Abstract: A method and a system for analyzing distinct light or radiation sources affecting a scene are provided. The method may include: sensing at least one image of a scene containing surfaces and objects, wherein the scene is illuminated by at least one distinct radiation or source; maintaining a database of the scene which stores approximate positions of at least some of the objects in the scene; identifying at least one candidate silhouette suspected to be cast by the at least one distinct light or radiation source, deriving properties of the at least one distinct light or radiation source, based on the at least one identified silhouette, based on data derived from the database.

Abstract: Methods and a system for identifying reflective surfaces in a scene are provided herein. The system may include a sensing device configured to capture a scene. The system may further include a storage device configured to store three-dimensional positions of at least some of the objects in the scene. The system may further include a computer processor configured to attempt to obtain a reflective surface representation for one or more candidate surfaces selected from the surfaces in the scene. In a case that the attempted obtaining is successful, computer processor is further configured to determine that the candidate reflective surface is indeed a reflective surface defined by the obtained surface representation. According to some embodiments of the present invention, in a case the attempted calculation is unsuccessful, determining that the recognized portion of the object is an object that is independent of the stored objects.

Abstract: Methods and systems for recalibrating sensing devices without using familiar targets are provided herein. The method may include: capturing a scene using a sensing device; determining whether or not the device is calibrated; in a case that said sensing device is calibrated, adding at least one new landmark to the known landmarks; in a case that said sensing device is not calibrated, determining at least some of the captured objects as objects stored on a database as known landmarks at the scene whose position is known; and calibrating the sensing device based on the known landmarks. The system may have various architectures that include a sensing device which captures images of the scene and further derive 3D data on the scene of some form.