17865762. METHOD AND APPARATUS WITH IMAGE INFORMATION GENERATION simplified abstract (Samsung Electronics Co., Ltd.)
METHOD AND APPARATUS WITH IMAGE INFORMATION GENERATION
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METHOD AND APPARATUS WITH IMAGE INFORMATION GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17865762 titled 'METHOD AND APPARATUS WITH IMAGE INFORMATION GENERATION
Simplified Explanation
The abstract describes a method that uses a neural network to generate final feature vectors for frames of a video and generate image information based on these vectors. The method determines whether to continue or stop processing each frame through the layers of the neural network and generates the final feature vector once the processing is complete.
- The method uses a neural network with multiple layers to process frames of a video.
- It generates final feature vectors for each frame, which represent important information about the frame.
- The method determines whether to continue processing a frame through the neural network or stop based on a sequenced operation.
- The final feature vector of a frame is generated once the corresponding sequenced operation completes its final stage.
Potential Applications
- Video analysis and understanding: The method can be used to extract important features from video frames, enabling applications such as video summarization, object recognition, and action recognition.
- Video compression: By generating compact and informative feature vectors, the method can aid in efficient video compression algorithms.
- Video editing: The generated image information can be used to automate or assist in video editing tasks, such as scene detection or content-based video retrieval.
Problems Solved
- Efficient video processing: The method optimizes the processing of video frames by determining when to stop or continue processing through the neural network, reducing computational overhead.
- Feature extraction: By generating final feature vectors, the method extracts important information from video frames, enabling various video analysis tasks.
Benefits
- Improved efficiency: The method's ability to determine when to stop processing frames reduces computational resources and speeds up video analysis tasks.
- Accurate feature extraction: The final feature vectors capture important information from video frames, leading to more accurate video analysis and understanding.
- Automation: The method automates the process of generating image information from video frames, reducing the need for manual intervention in tasks like video editing or analysis.
Original Abstract Submitted
A method includes generating, by a neural network having a plurality of layers, final feature vectors of one or more frames of a plurality of frames of an input video, while sequentially processing each of the plurality of, and generating image information corresponding to the input video based on the generated final feature vectors. For each of the plurality of frames, the generating of the final feature vectors comprises determining whether to proceed with or stop a corresponding sequenced operation through layers of the neural network for generating a final feature vector of a corresponding frame, and generating the final feature vector of the corresponding frame in response to the corresponding sequenced operation completing a final stage of the corresponding sequenced operation.
