Abstract: A simultaneous localization and mapping method and corresponding system are disclosed. The method comprises: receiving a frame of three dimensional point cloud data from a three dimensional point cloud sensor coupled to a robot; receiving inertial measurement data indicative of a change in pose of the three dimensional point cloud sensor; using the inertial measurement data to estimate a rotation between the received frame of three dimensional point cloud data and a key frame of three dimensional point cloud data; applying a rotation to the received frame of three dimensional point cloud data to obtain an aligned frame of three dimensional point cloud data, the aligned frame of three dimensional point cloud data having an orientation aligned with the key frame of three dimensional point cloud data; and estimating a translation of the aligned frame of three dimensional point cloud data from the key frame of three dimensional point cloud data.

Abstract: A simultaneous localization and mapping method and corresponding system are disclosed. The method comprises: receiving a frame of three dimensional point cloud data from a three dimensional point cloud sensor coupled to a robot; receiving inertial measurement data indicative of a change in pose of the three dimensional point cloud sensor; using the inertial measurement data to estimate a rotation between the received frame of three dimensional point cloud data and a key frame of three dimensional point cloud data; applying a rotation to the received frame of three dimensional point cloud data to obtain an aligned frame of three dimensional point cloud data, the aligned frame of three dimensional point cloud data having an orientation aligned with the key frame of three dimensional point cloud data; and estimating a translation of the aligned frame of three dimensional point cloud data from the key frame of three dimensional point cloud data.

Abstract: Classification of a group of temporally related images is disclosed, wherein a capture-location sequence is identified from the group of temporally related images. The capture-location-sequence information, which is associated collectively with the capture-location sequence, is compared with each of a plurality of sets of predetermined capture-location-sequence characteristics. Each set is associated with a predetermined classification. An identified classification associated with the group of temporally related images is identified based at least upon results from the comparing step; and the identified classification is stored in a processor-accessible memory system.

Abstract: Described is a technology by which video is processed to determine whether the video contains a specified action. The video corresponds to a spatial-temporal volume. The volume is searched to find a sub-volume therein that has a maximum score with respect to whether the video contains the action. Searching for the sub-volume is performed by separating the search space into a spatial subspace and a temporal subspace. The spatial subspace is searched for an optimal spatial window using upper-bounds searching. Also described is discriminative pattern matching.

Abstract: Classification of a group of temporally related images is disclosed, wherein a capture-location sequence is identified from the group of temporally related images. The capture-location-sequence information, which is associated collectively with the capture-location sequence, is compared with each of a plurality of sets of predetermined capture-location-sequence characteristics. Each set is associated with a predetermined classification. An identified classification associated with the group of temporally related images is identified based at least upon results from the comparing step; and the identified classification is stored in a processor-accessible memory system.

Abstract: A method, apparatus, and electronic device for searching for repetitive video content are disclosed. A memory may store a set of video data. A processor may match a premier query window to a trellis match video window of the set of video data. The processor may compare a successive query window to a successive trellis match video window. The processor may disregard the trellis match video window if the successive trellis match video window does not match the successive query window.