Facial Summary Video Representative Image Generation
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Solution Overview
Problem
Existing methods for representing videos often result in representative images where people are difficult to see due to small size or lack of close-up frames, especially in videos with multiple shots, leading to incomplete information being included.
Innovation Solution
A process for generating a facial summary image that includes face detection, grouping, and selecting prominent faces based on detection frequency, size, and importance values, with optional use of pre-selected headshots, to create a visually appealing and informative image summarizing the video content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single frame is selected as the representative image, then the process is simple and fast, but the people in the image are difficult to see and information from multiple shots is lost
Solution Approach 1:
The video is divided into multiple shots, and faces are detected and extracted from each shot separately. Multiple representative faces from different shots are then combined into a single composite image, ensuring that information from all shots is preserved while maintaining generation efficiency through automated processing.
Solution Approach 2:
Faces detected from multiple different shots are merged into a single representative image. The system combines multiple face images that appear across different video shots, creating a comprehensive representative image that includes all prominent individuals rather than selecting just one frame.
2Device complexity
If a single frame is selected as the representative image, then the processing is simple, but the representative image does not include information from all shots
Solution Approach 1:
The video content is segmented into multiple shots, and face detection is performed independently on each shot. This segmentation allows the system to identify faces from all shots without requiring complex inter-shot analysis, maintaining relatively simple processing while ensuring comprehensive information capture.
Solution Approach 2:
The face detection and extraction process is designed to work universally across multiple shots with different characteristics. The same detection algorithm is applied to each shot regardless of its content or timing, enabling the system to consistently extract faces from diverse video segments and combine them into a single representative image.
3Loss of information
If face detection and grouping is performed to create a facial summary, then visibility and inclusivity of video content is enhanced, but the processing complexity increases
Solution Approach 1:
The system automatically performs face detection, grouping, and selection without requiring manual intervention. Face images are automatically detected from multiple shots, grouped by similarity, and the most representative faces are automatically selected based on detection frequency and visual characteristics, reducing the need for complex manual processing while enhancing visibility and inclusivity.
Solution Approach 2:
Manual frame selection and image composition is replaced with automated computer vision algorithms. The system uses machine learning-based face detection and recognition to automatically identify, extract, and compose representative faces from multiple shots, substituting manual mechanical processes with intelligent automated systems that enhance information retention while managing complexity through algorithmic efficiency.
Data Source
AI summary
A plurality of sets of face images associated with a video is obtained. Each set of face images corresponds to a particular person depicted in the video. Of the people associated with the plurality of sets of face images, one or more of those people are selected to be included in a facial summary by analyzing the plurality of sets of face images and/or the video. For each of the selected one or more people, a face image to use in the facial summary is selected. The facial summary is laid out using the selected face images.