The Consumer Digital Video Library
CDVL is a digital video library intended for researchers and developers in the fields of
video processing and visual quality (both objective and subjective assessment).
Progress in these areas have been limited by the availability of high quality royalty-free
test material. CDVL provides relevant video clips for different types of video processing
and quality measurement applications. This fills a critical industry need.
The Concept and Goal
CDVL’s goal is to support and maintain a repository of content and knowledge that will
facilitate and foster collaborative research and development in the area of consumer video
processing and quality measurement. CDVL accepts and shares contributions of video content
that are most relevant for determining the effectiveness of consumer video processing
applications (e.g. corrective/reconstructive processing, enhancement, and re-formatting)
and quality measurement algorithms. Video clips can be downloaded for the purpose of assessing
visual quality using subjective or objective methods and the results can then be shared with
other CDVL users. Video clips can be accessed through a browse and search type of interface
that incorporates clip descriptors (e.g., resolution, scanning format, frame rate, chroma sampling
structure, content type, coding complexity, etc.) as well as recommended usage guidance
(e.g., users may find candidate 1080i video clips that are suitable for de-interlacing
applications). CDVL fosters a collaborative approach to maintaining high quality original
source content as well as a sharing of research results in the areas of consumer video processing
and quality evaluation.
Why Not Join? It's Free!
Registered CDVL users have access to high quality uncompressed video scenes that may be used freely for research and development purposes. Users may also contribute their videos to the CDVL database.
- High Quality Uncompressed Videos
- Subjectively Rated Videos
Typical Industry Uses
- Choosing Video Equipment
- Optimizing Video System Performance
- Improving Video Coding Algorithms
- Developing Objective Video Quality Models
- Quantifying Video Processing Algorithm Improvements
- Conducting Subjective Video Quality Tests