Samsung electronics co., ltd. (20240221185). METHOD AND APPARATUS WITH TARGET OBJECT TRACKING simplified abstract
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 20240221185 titled 'METHOD AND APPARATUS WITH TARGET OBJECT TRACKING
Simplified Explanation:
The patent application describes a method for tracking a target object in an input image using a neural network model. The method involves setting a search area based on a target box in a template image, selecting a network path based on resizing ratios, and estimating the position of the target object in the input image.
- The method involves setting a search area for a target object in an input image based on a position of a target box in a template image.
- It selects a network path from a neural network model based on resizing ratios of input images.
- The target object is tracked by estimating the position of a target box in the input image using the selected network path.
Key Features and Innovation:
- Target object tracking in input images using neural network models.
- Adaptive selection of network paths based on resizing ratios.
- Estimation of target object position for tracking purposes.
Potential Applications:
- Surveillance systems
- Autonomous vehicles
- Augmented reality applications
Problems Solved:
- Efficient target object tracking in complex environments.
- Adaptation to varying input image sizes.
- Real-time object tracking capabilities.
Benefits:
- Improved accuracy in target object tracking.
- Enhanced performance in dynamic scenarios.
- Scalability for different applications.
Commercial Applications:
- Security and surveillance industry for tracking individuals or objects.
- Automotive industry for autonomous driving systems.
- Entertainment industry for augmented reality experiences.
Questions about Target Object Tracking Technology:
1. How does the method adapt to different input image sizes for target object tracking? 2. What are the key advantages of using neural network models for object tracking in images?
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.
