.png){kind=icon}
.png){kind=icon}
Return
Toward Visualization and Searching: A Dual-Purpose Video Coding Framework
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2966692.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
To offer more powerful video-enabled applications, it is increasingly more critical not only to visualize the decoded video but also to provide efficient searching capabilities for similar content. Video surveillance and personal communication are critical application examples asking for these dual visualization and searching functionalities. However, the current video coding solutions are strongly biased towards visualization needs. In this context, this paper introduces a novel dual-purpose video coding framework targeting both visualization and searching needs by adopting a hybrid coding approach where the usual pixel-based coding approach is combined with an innovative feature-based coding approach. In a particular implementation of this dual-purpose video coding framework, some frames are coded using a set of keypoint matches, which not only allow decoding for visualization, but also provide the decoder valuable feature-related information, extracted at the encoder from the original frames, instrumental for efficient searching. Experimental results for video surveillance and personal communications scenarios show competitive performance regarding the state-of-the-art HEVC standard both in terms of visualization and searching performances.
Keywords:
Descriptor
dual-purpose video coding
HEVC
keypoint
matching
searching
visualization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
View more organizations