Intel has patented a method to divide spatial data into segments based on dimension coordinates, detect objects within each segment, and combine the detected objects into a unified list. This innovation enhances object detection processes for improved efficiency and accuracy. GlobalData’s report on Intel gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Intel, Device power optimization was a key innovation area identified from patents. Intel's grant share as of January 2024 was 58%. Grant share is based on the ratio of number of grants to total number of patents.
Spatial data segmentation and object detection system
A recently granted patent (Publication Number: US11887377B2) discloses an apparatus and method for object detection in spatial data, particularly designed for autonomous vehicles. The apparatus includes a memory to store spatial data with coordinates in three dimensions and a processor to divide the data along the second dimension axis, execute object detection processes on segmented data, and generate a unified list of objects by combining detected objects from different segments. The apparatus further includes features like overlapping data segments, identification of objects within overlapping segments, and combining objects from multiple segments to enhance object detection accuracy.
Moreover, the patent describes a method and a machine-readable storage medium with instructions to access spatial data, segment it based on the second dimension, perform object detection processes on each segment, and combine detected objects to create a unified list. The disclosed technology is particularly relevant for autonomous vehicles, where accurate object detection is crucial for safe navigation. By dividing the spatial data into segments and combining detected objects, the apparatus and method aim to improve the efficiency and accuracy of object detection processes, especially in complex environments. Additionally, the patent highlights the use of LiDAR technology and sensors to obtain spatial data, emphasizing the importance of advanced sensing technologies in autonomous vehicle applications.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
