Video Streaming Summaries Using Motion Detection and Variable Frame Rates
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Solution Overview
Problem
Existing video monitoring systems lack efficient methods for automatically creating summaries of webcam video content, particularly in identifying and prioritizing important events, leading to unnecessary data storage and high bandwidth usage.
Innovation Solution
A remote video camera system that intermittently transmits video clips and still images to a remote server, using artificial intelligence and image recognition to focus on important events, creating a weighted video summary with varying time-lapse speeds and contextual tags, and streaming at lower bandwidth with higher resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If continuous video streaming is used to monitor all events, then complete video coverage is achieved, but bandwidth usage increases significantly
Solution Approach 1:
The system extracts only the essential information from continuous video streams by detecting motion events and generating condensed summaries that capture key moments. This extraction process removes redundant data while preserving important information, resolving the contradiction between complete coverage and bandwidth efficiency.
Solution Approach 2:
The system changes the temporal parameter of video transmission by using variable frame rates and time-lapse techniques for different segments. Important events are captured at full resolution while less critical periods are summarized, transforming the uniform continuous stream into a variable-rate representation that maintains information quality while reducing bandwidth consumption.
2Manufacturing precision
If high resolution video is transmitted at full frame rate, then video quality is maintained, but data transmission volume increases
Solution Approach 1:
The system dynamically adjusts video transmission parameters based on event importance and temporal context. During motion events, full resolution is maintained, while during static periods, the system transitions to lower resolution or summary representations, creating a dynamic adaptation that preserves quality when needed and reduces data volume when appropriate.
Solution Approach 2:
The system implements periodic sampling of video content at variable intervals based on detected motion and event significance. Instead of continuous full-resolution transmission, the system periodically captures key moments and interpolates or summarizes intermediate periods, maintaining perceived quality while dramatically reducing overall data transmission volume.
3Loss of information
If all video data is stored for review, then complete analysis capability is achieved, but storage requirements increase
Solution Approach 1:
The system segments video data into distinct event-based units with hierarchical organization. Instead of storing uniform continuous video, the system identifies and segments important events, storing them at full quality while representing inter-event periods through compressed summaries or metadata, enabling complete analysis capability with reduced storage requirements through intelligent data segmentation.
Data Source
AI summary
In one embodiment of the present invention, a video camera selectively streams to a remote server. Still images or short video events are intermittently transmitted when there is no significant motion detected. When significant motion is detected, video is streamed to the remote server. The images and video can be higher resolution than the bandwidth used, by locally buffering the images and video, and transmitting it at a lower frame rate that extends to when there is no live streaming. This provides a time-delayed stream, but with more resolution at lower bandwidth.