17820863. MOTION VECTOR (MV) CANDIDATE REORDERING simplified abstract (QUALCOMM Incorporated)
MOTION VECTOR (MV) CANDIDATE REORDERING
Organization Name
Inventor(s)
Yao-Jen Chang of San Diego CA (US)
Han Huang of San Diego CA (US)
Vadim Seregin of San Diego CA (US)
Chun-Chi Chen of San Diego CA (US)
Marta Karczewicz of San Diego CA (US)
MOTION VECTOR (MV) CANDIDATE REORDERING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17820863 titled 'MOTION VECTOR (MV) CANDIDATE REORDERING
Simplified Explanation
Abstract Explanation
The patent application describes a system and method for coding video data. It involves obtaining prediction candidates associated with the video data, grouping them using a grouping method, reordering the group, and selecting a merge candidate to be added to a candidate list.
- Obtaining a first set of prediction candidates for video data
- Grouping the prediction candidates using a grouping method
- Reordering the grouped prediction candidates
- Selecting a merge candidate from the reordered group
- Adding the merge candidate to a candidate list
Potential Applications
- Video compression and encoding technologies
- Video streaming platforms
- Video editing software
- Video surveillance systems
Problems Solved
- Efficient coding of video data
- Improved video compression techniques
- Enhanced video streaming quality
- Streamlined video editing processes
- Optimal utilization of video surveillance storage
Benefits
- Higher video compression ratios
- Reduced bandwidth requirements for video streaming
- Faster video editing workflows
- Improved video surveillance storage efficiency
- Enhanced video quality for various applications
Original Abstract Submitted
Systems and techniques are provided for coding video data. In some examples, a process may include obtaining a first plurality of prediction candidates associated with video data. The process may further include determining a first group of prediction candidates at least in part by applying a first grouping method to the first plurality of prediction candidates. The process may include reordering the first group of prediction candidates and selecting a first merge candidate from the reordered first group of prediction candidates. The process may further include adding the first merge candidate to a candidate list.
