Camera Object Detection Bandwidth Reduction via Video Stream Cropping
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Solution Overview
Problem
In camera surveillance, transmitting full-resolution video streams for object detection and analysis consumes significant bandwidth, as the required computational power for real-time analysis is typically not available in cameras, necessitating remote server analysis but increasing network usage.
Innovation Solution
A method where cameras detect and crop interesting objects within video frames, transmitting only these cropped areas as part of a continuous video stream, reducing bandwidth usage by incorporating predetermined background content and potentially scaling or adjusting the crops for efficient data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full-resolution video stream is transmitted for object detection and analysis, then detection quality is improved, but network bandwidth consumption increases significantly
Solution Approach 1:
The video stream is segmented into full-resolution background frames and cropped object regions. The background is transmitted at low resolution or as static images, while only the cropped object areas are transmitted at full resolution. This segmentation allows the system to maintain high detection quality for objects while significantly reducing overall bandwidth consumption.
Solution Approach 2:
The patent extracts and transmits only the relevant object portions from the full video stream. By detecting objects in the video and cropping their regions of interest, the system extracts only the necessary data for analysis, eliminating the need to transmit the entire full-resolution video stream and thus reducing bandwidth requirements.
2Speed
If computational power for real-time object analysis is available in the camera, then analysis speed is improved, but device complexity and cost increase
Solution Approach 1:
The computational tasks are segmented and distributed: the camera performs simple object detection and cropping operations, while the server performs complex analysis such as object identification, tracking, and recognition. This segmentation of computational workloads allows real-time analysis without requiring high computational power in the camera itself.
Solution Approach 2:
The patent introduces a server as an intermediary between the camera and the analysis system. The camera transmits cropped object regions to the server, which then performs the computationally intensive analysis. This intermediary approach enables fast and accurate object analysis while keeping the camera device simple and affordable.
3Quantity of substance
If only cropped object areas are transmitted instead of full video stream, then network bandwidth consumption is reduced, but data completeness may be compromised
Solution Approach 1:
The system performs preliminary object detection and cropping before transmission. By pre-identifying objects of interest and extracting their regions, the system ensures that the transmitted data contains all necessary information for analysis while minimizing unnecessary data transfer. This preliminary action maintains data completeness for the relevant objects without wasting bandwidth on background data.
Data Source
AI summary
A computer-implemented method in a processor device of a camera, the method comprising: acquiring image frames comprising video data, communicating with a receiver device for continuously transmitting a video stream to the receiver device over a communication network; detecting at least one object in the image frames of the video data, the detected at least one object belong to at least one predetermined object class selected as surveillance target; cropping sub-areas in the image frames of the video data, the sub-areas including the at least one detected object, and adding the cropped sub-areas to image frames of the video stream being continuously transmitted as a single video stream to the receiver device.