Content-Aware Video Retargeting With Pixel-Accurate Warp
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Solution Overview
Problem
Conventional video retargeting techniques fail to provide a comfortable viewing experience due to unnatural object proportions and visible discontinuities, especially when scaling video content for devices with different display formats, as they lack uniform scaling and temporal coherence.
Innovation Solution
An integrated system for content-aware video retargeting that combines key frame-based constraint editing with automatic algorithms, using a non-uniform, pixel-accurate warp that considers video saliency, edge preservation, and scene cut detection, along with interactive constraints to enforce bilateral temporal coherence, and employs elliptical weighted average splatting for aliasing reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If naive linear downscaling is used to fit video content to target platform frame size, then the video can be played back on devices with different display formats, but the object proportions appear unnatural and viewing experience is uncomfortable
Solution Approach 1:
The patent applies different scaling behaviors to different regions of the video frame. Important content regions are preserved with accurate proportions while less important regions are scaled or cropped. This is achieved through content-aware algorithms that identify and protect salient objects, maintaining their aspect ratios independently from the overall frame scaling.
Solution Approach 2:
The video frame is segmented into important and unimportant regions based on content analysis. The patent identifies salient objects, faces, and key scene elements, then applies different retargeting operations to different segments. This allows critical content to maintain proper proportions while enabling format adaptation through scaling or cropping of non-critical areas.
2Adaptability or versatility
If cropping or panning techniques are used to remove unimportant content, then the video fits better within target format, but temporal coherence is lost and viewing experience deteriorates
Solution Approach 1:
The patent employs dynamic retargeting where the cropping and scaling operations adapt frame-by-frame based on content analysis. The system continuously identifies important regions and adjusts the retargeting parameters dynamically to maintain temporal coherence. This ensures that important objects remain visible and properly proportioned across scene transitions and camera movements.
Solution Approach 2:
The system performs preliminary identification and tracking of important content regions before applying retargeting operations. By pre-identifying salient objects and their trajectories, the system can plan retargeting operations that maintain temporal coherence, ensuring smooth transitions and consistent object representation across frames.
3Adaptability or versatility
If manifold seam techniques are used to remove insignificant pixels, then large scale changes can be achieved, but visible discontinuities and aliasing artifacts occur
Solution Approach 1:
The patent employs advanced interpolation and filtering parameters to smooth transitions in retargeted video. By adjusting scaling algorithms, anti-aliasing filters, and edge preservation parameters, the system achieves high-quality scaling without visible discontinuities. The system dynamically selects optimal processing parameters based on content characteristics and target format requirements.
4Adaptability or versatility
If conventional video retargeting approaches are used, then video can be converted to different formats, but uniform scaling of important image content is not achieved
Solution Approach 1:
The patent applies uniform scaling specifically to important feature regions while allowing different scaling behavior in other areas. Content-aware algorithms identify salient objects and enforce consistent aspect ratios and scaling factors for these regions, while less important areas can be scaled or cropped to achieve format compatibility. This selective approach maintains both format adaptability and feature region accuracy.
Data Source
AI summary
Techniques are provided for content-aware video retargeting. An interactive framework combines key frame-based constraint editing with numerous automatic algorithms for video analysis. This combination gives content producers a high level of control of the retargeting process. One component of the framework is a non-uniform, pixel-accurate warp to the target resolution that considers automatic as well as interactively-defined features. Automatic features comprise video saliency, edge preservation at the pixel resolution, and scene cut detection to enforce bilateral temporal coherence. Additional high level constraints can be added by the producer to achieve a consistent scene composition across arbitrary output formats. Advantageously, embodiments of the invention provide a better visual result for retargeted video when compared to using conventional techniques.