Búsqueda por similitud de vídeos
Potencie su sistema de búsqueda de similitudes de vídeo con la base de datos vectorial Zilliz Cloud (totalmente gestionada Milvus)
Video Similarity Search With Zilliz Cloud Vector Database
Discover videos resembling your video query with Zilliz Cloud-powered video search engines, proven beneficial for video surveillance, deduplication, recommendation, and beyond.
High-Performant Video Search with Unparalleled Precision
Experience a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency. Benefit from unparalleled precision using hybrid vector search with scalar filtering and range search capability.
Efficiently Managing Your Spiking Video Search Data
Say goodbye to data size concerns with Zilliz Cloud. Experience horizontal and independent scaling for computing and storage, aligning with your budget and evolving needs.
Real-Time Responses for Optimized User Experience
Zilliz Cloud guarantees consistently up-to-date search results through real-time data insertion, deletion, and seamless data flows, significantly optimizing the user experience.
Always On, Always Reliable
Zilliz Cloud builds resilient video search systems, guaranteeing uninterrupted service reliability, even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Simple Start, Amplified Productivity
Deploy a large-scale similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive user experience.
Cómo Zilliz Cloud potencia la búsqueda por similitud de vídeos
Un sistema de búsqueda de similitudes de vídeo basado en Zilliz funciona de la siguiente manera:
- Los vídeos se transforman en incrustaciones vectoriales utilizando un modelo de incrustación.
- Las incrustaciones de vídeo se ingieren y almacenan en Zilliz Cloud.
- Un usuario busca vídeos similares a su vídeo.
- La consulta de vídeo se transforma en incrustaciones vectoriales utilizando un modelo de incrustación.
- Las incrustaciones de la consulta se envían a Zilliz Cloud para realizar una búsqueda de similitudes.
- Zilliz Cloud realiza búsquedas RNA y recupera los K resultados más relevantes.
- Zilliz Cloud devuelve al usuario los K resultados más relevantes.
Historias de Éxito
Los líderes del sector de todo el mundo utilizan Milvus o Zilliz Cloud (el Milvus totalmente gestionado) para impulsar su negocio de búsqueda de vídeos.
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
Leer Ahora<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
Leer Ahora<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance