18078634. Detecting Portions of Images Indicative of the Presence of an Object simplified abstract (Google LLC)
Contents
Detecting Portions of Images Indicative of the Presence of an Object
Organization Name
Inventor(s)
Skirmantas Kligys of Manhattan Beach CA (US)
Wen-Sheng Chu of Santa Clara CA (US)
Xiaoming Liu of Mountain View CA (US)
Detecting Portions of Images Indicative of the Presence of an Object - A simplified explanation of the abstract
This abstract first appeared for US patent application 18078634 titled 'Detecting Portions of Images Indicative of the Presence of an Object
The patent application describes systems and methods for detecting objects in images using segmentation and convolutional models.
- The method involves analyzing an input image to identify indicative areas that suggest the presence of objects.
- A convolutional model is then used to label these areas and determine if specific objects are present in the image.
- Actions are taken based on the labels generated by the convolutional model.
Potential Applications:
- Object detection in security systems
- Autonomous driving for identifying obstacles
- Medical imaging for identifying anomalies in scans
Problems Solved:
- Efficient and accurate object detection in images
- Automation of object recognition tasks
- Improved image analysis in various fields
Benefits:
- Enhanced image processing capabilities
- Increased accuracy in object detection
- Time-saving automation of object recognition tasks
Commercial Applications:
- Security systems for object detection
- Autonomous vehicles for obstacle recognition
- Medical imaging for anomaly detection
Questions about Object Detection Technology: 1. How does this technology improve upon traditional image recognition methods? 2. What are the key advantages of using segmentation and convolutional models for object detection?
Original Abstract Submitted
Provided are systems and methods for detecting an object in an image. The method can include receiving an input image and analyzing the input image using an image segmentation model to identify one or more indicative areas within the input image, the one or more indicative areas being indicative of one or more objects within the input image. The method can also include analyzing the one or more indicative areas of the input image using a convolutional model to generate at least one label for at least one portion of the one or more indicative areas of the input image, the label indicating whether a specific object is identified within the input image, and performing at least one action based on the at least one label for the at least one portion.
