Video processing for occupancy detection

A video stream, pixel technology, applied in the field of computing

Active Publication Date: 2018-03-27
ANALOG DEVICES INT UNLTD
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

These two design goals can make it challenging to provide algorithms that are computationally efficient and can accurately detect human presence.

Method used

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  • Video processing for occupancy detection
  • Video processing for occupancy detection
  • Video processing for occupancy detection

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Embodiment Construction

[0016] The basis for detecting the presence of people in video streams

[0017] Computer vision algorithms for detecting human presence can be varied, with their own drawbacks and advantages. One technique detects the presence of a person by determining whether there is activity in the foreground, i.e. by comparing the frame with the background. Another technique detects the presence of a person by determining whether there is motion, i.e. by comparing a frame with a previous frame. Both foreground-based and motion-based techniques are simple, but either technique can generate false positives when there are moving non-human objects in the video stream, such as moving plants, tethered balloons moving through the air, and spinning fans. Therefore, neither technique can be used outdoors. While another technique detects human presence by analyzing frames for silhouette, shape, color or other signatures. Due to complex image processing algorithms, this technique can be computa...

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Abstract

Many conventional video processing algorithms attempting to detect human presence in a video stream often generate false positives on non-human movements such as plants moving in the wind, rotating fan, etc. To reduce false positives, a technique exploiting temporal correlation of non-human movements can accurately detect occupancy while reject non-human movements. Specifically, the technique involves performing temporal analysis on a time-series signal generated based on an accumulation of foreground maps and an accumulation of motion map and analyzing the running mean and the running variance of the time-series signal. By determining whether the time-series signal is correlated in time, the technique is able to distinguish human movements and non-human movements. Besides having superioraccuracy, the technique lends itself to an efficient algorithm which can be implemented on low cost, low power digital signal processor or other suitable hardware.

Description

[0001] priority data [0002] This application claims priority to US Patent Application Serial No. 14 / 794,991, entitled "Video Processing for Human Occupancy Detection," filed July 9, 2015, the entire contents of which are hereby incorporated by reference. technical field [0003] The present invention relates to the field of computing, and more particularly to video processing for occupancy detection. Background technique [0004] Computer vision is the field of computing concerned with applying algorithms to video streams to gain an understanding of the activity present in the video stream. Among them, an important application is surveillance, which requires detection of human presence in video streams. Video processing is computationally intensive. At the same time, algorithms need to accurately detect the presence of people. These two design goals can make it challenging to provide algorithms that are computationally efficient and capable of accurately detecting human...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T7/20
CPCG06V40/103G06V20/59G06V20/52G06T2207/10016G06T2207/30196
Inventor S·拉卡
Owner ANALOG DEVICES INT UNLTD
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