San Jose, CA, United States of America

Rubén Aciego Casero

This inventor holds 1 USPTO granted patent and 6 published patent applications. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Rubén Aciego Casero. Retrieved from https://idiyas.com/inventor/rubén-aciego-casero

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Rubén Aciego Casero: Video-Encoding Patent

Introduction

Rubén Aciego Casero is an inventor associated with San Jose, California. His patent work addresses techniques for choosing quantization methods when encoding video data.

Latest Patents

The provided information identifies one patent associated with Aciego Casero: “Techniques for Selecting Between Scalar Quantization and Trellis Coded Quantization When Encoding Video Data.” The invention describes an encoder that receives transform coefficients for prediction residues in video data and sets a flag based on metadata or statistics about those coefficients. Depending on the flag, the encoder applies trellis coded quantization or scalar quantization, then entropy-codes the resulting quantization indices to produce encoded video data.

Career Highlights

Aciego Casero’s listed patent focuses on selecting between two quantization approaches within a video encoder. The technique uses information about the transform coefficients to guide that choice. The supplied data lists 1 patent.

Collaborations

The provided information names Xiaoqing Zhu and Andrey Norkin as coworkers associated with Aciego Casero.

Conclusion

Rubén Aciego Casero’s listed invention concerns adaptive quantization selection for video encoding, using coefficient-related information to guide encoding operations.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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