Frame level feature aggregation method for video target detection

A target detection and aggregation method technology, applied in the field of computer vision, can solve the problems of high false detection rate and missed detection rate, inability to accurately detect moving targets, etc.

Active Publication Date: 2019-07-09
NORTHEASTERN UNIV
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Problems solved by technology

In complex scenes such as motion blur, low pixels, lens zoom, occlusion, etc., the above methods cannot accurately ...

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  • Frame level feature aggregation method for video target detection
  • Frame level feature aggregation method for video target detection
  • Frame level feature aggregation method for video target detection

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Embodiment Construction

[0063] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0064] In this embodiment, a certain video data set is taken as an example, and a frame-level feature aggregation method oriented to video target detection of the present invention is used to aggregate the frame-level features of the video data;

[0065] A frame-level feature aggregation method for video object detection, such as figure 1 and figure 2 shown, including the following steps:

[0066] Step 1: Frame level feature extraction;

[0067] Use ResNet-101 as the feature network of the entire detection framework to extract deep features from a single frame image;

[0068] Given the current frame i and the two frames i-t, i+t adjacent to the current frame, where t ...

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Abstract

The invention provides a frame level feature aggregation method for video target detection, and relates to the technical field of computer vision. The invention provides a frame-level feature aggregation method for video target detection. The method comprises the following steps: firstly, extracting deep features from a single-frame image through a feature network; extracting an inter-frame optical flow by using an optical flow network FlowNet; aligning the frame-level features of the adjacent frames to the current frame based on the optical flow to realize frame-level feature propagation; finally, calculating the scaling cosine similarity weight through the mapping network and the weight scaling network, and using the scaling cosine similarity weight to aggregate the multi-frame featuresto generate the aggregated features. According to the frame-level feature aggregation method for video target detection provided by the invention, the weight distribution is more reasonable, and the aggregated features are input into the video target detection network, so that video detection in complex scenes such as motion blur, low pixels, lens zooming and shielding can have a better detectioneffect and robustness.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a frame-level feature aggregation method for video target detection. Background technique [0002] In recent years, with the rise of deep learning, video object detection has gradually developed rapidly. Since target detection in video has more temporal context information and motion information than target detection in a single image, many studies have used this information to improve the performance of video target detection. The video target detection method automatically analyzes and processes the video sequences collected by the camera, and then realizes the detection, classification, recognition and tracking of moving targets in the monitoring scene. Most existing feature-level video object detection methods use frame-level feature aggregation methods. The purpose of frame-level feature aggregation is to use the time and motion information between video frames to ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/08
CPCG06N3/08G06V20/42G06V20/46
Inventor 张斌柳波郭军刘晨王嘉怡李薇张娅杰王馨悦刘文凤陈文博侯帅
Owner NORTHEASTERN UNIV
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