18584794. TECHNIQUES FOR TRACKING ONE OR MORE OBJECTS simplified abstract (Apple Inc.)
Contents
TECHNIQUES FOR TRACKING ONE OR MORE OBJECTS
Organization Name
Inventor(s)
Onur E. Tackin of Saratoga CA (US)
Dhruv Samant of Mountain View CA (US)
Mahmut Demir of Dublin CA (US)
Samuel D. Post of Great Falls MO (US)
TECHNIQUES FOR TRACKING ONE OR MORE OBJECTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18584794 titled 'TECHNIQUES FOR TRACKING ONE OR MORE OBJECTS
Simplified Explanation: The patent application describes methods for tracking objects using data from multiple modalities and predicting their positions.
- Receiving data from different sources about the object
- Receiving image data of the field of view without object data
- Predicting the object's position using the collected data
Key Features and Innovation:
- Utilizes data from multiple modalities for object tracking
- Predicts object position based on received data
- Excludes object data from field of view image data for prediction
Potential Applications:
- Surveillance systems
- Autonomous vehicles
- Augmented reality applications
Problems Solved:
- Enhanced object tracking accuracy
- Improved prediction of object positions
- Integration of data from different sources for tracking
Benefits:
- Increased efficiency in object tracking
- Enhanced accuracy in predicting object positions
- Improved overall system performance
Commercial Applications: The technology can be applied in various industries such as security, transportation, and entertainment for efficient object tracking and prediction.
Prior Art: Readers can explore prior research on object tracking methods using data from multiple modalities to understand the evolution of this technology.
Frequently Updated Research: Stay updated on the latest advancements in object tracking technology using data from various sources for improved accuracy and efficiency.
Questions about Object Tracking Technology: 1. How does the integration of data from multiple modalities improve object tracking accuracy? 2. What are the potential challenges in predicting object positions accurately using this technology?
Original Abstract Submitted
Some methods are described herein for tracking one or more objects. In some examples, the method is performed at a computer system. In some examples, the method includes receiving a first set of data corresponding to the object via a first modality and a second set of data corresponding to the object via a second modality; after receiving the first set of data corresponding to the object and the second set of data corresponding to the object, receiving a second set of image data representing the field of view of the camera, wherein the second set of image data does not include data representative of the object; and after receiving the second set of image data, predicting a position of the object using at least the first set of data corresponding to the object and the second set of data corresponding to the object.
