18352636. METHOD AND APPARATUS WITH TARGET OBJECT TRACKING simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
METHOD AND APPARATUS WITH TARGET OBJECT TRACKING
Organization Name
Inventor(s)
Changbeom Park of Suwon-si (KR)
METHOD AND APPARATUS WITH TARGET OBJECT TRACKING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18352636 titled 'METHOD AND APPARATUS WITH TARGET OBJECT TRACKING
The patent application describes a processor-implemented method for target object tracking using a neural network model.
- Setting a search area for a target object in an input image based on the position of a first target box in a template image.
- Selecting a network path from multiple paths in the neural network model based on the resizing ratio of another input image.
- Tracking the target object by estimating the position of a second target box in the input image using the selected network path.
Potential Applications: - Surveillance systems - Autonomous vehicles - Robotics - Augmented reality
Problems Solved: - Efficient target object tracking in images - Improved accuracy in object localization
Benefits: - Enhanced object tracking capabilities - Increased efficiency in image analysis tasks
Commercial Applications: Title: Advanced Object Tracking Technology for Surveillance Systems This technology can be utilized in surveillance systems to enhance security measures and improve tracking of individuals or objects in real-time. It can also be integrated into autonomous vehicles for better navigation and obstacle avoidance.
Questions about Target Object Tracking: 1. How does this technology improve object tracking accuracy compared to traditional methods? This technology utilizes neural networks to dynamically adjust network paths based on resizing ratios, leading to more accurate object localization. 2. What are the potential limitations of using neural networks for object tracking? Neural networks may require significant computational resources and training data to achieve optimal performance.
Original Abstract Submitted
A processor-implemented method with target object tracking includes: setting a search area for a target object included in an input image based on a position of a first target box in a template image; selecting a network path from a plurality of network paths of a neural network model according to a resizing ratio of a size of another image that is input to the neural network model to a size of the search area; and tracking the target object by estimating a position of a second target box corresponding to the target object in the input image according to the selected network path.
