US 2016/0239982 A1 · HIGH-SPEED AUTOMATIC MULTI-OBJECT TRACKING METHOD AND SYSTEM WITH KERNELIZED CORRELATION FILTERS

Abstract

A high-speed automatic multi-object tracking method with kernelized correlation filters is provided. The method includes obtaining an image frame from a plurality of image frames in a video, extracting a foreground object sequence from the obtained image frame, and determining similarity between each foreground object of the extracted foreground object sequence and a tracked object. The method also includes calculating HOG features of the foreground objects with a lower similarity, obtaining training samples for each of the foreground objects with the lower similarity using a circular matrix, obtaining a classifier via a kernel method accelerated by FFTW, and obtaining tracking points using a sparse optical flow. Further, the method includes detecting object matching responses using a detection response function, performing multi-scale analysis for the object based on an optical flow method, and processing a next image frame of the plurality of image frames in the video until the video ends.

Claims10

Dependent claims

A high-speed automatic multi-object tracking method with kernelized correlation filters implemented by an object tracking system, comprising:

obtaining an image frame from a plurality of image frames in a video;
extracting a foreground object sequence from the obtained image frame;
determining similarity between each foreground object of the extracted foreground object sequence and a tracked object;
calculating Histogram of Oriented Gradients (HOG) features of the foreground objects with a lower similarity;
obtaining training samples for each of the foreground objects with the lower similarity using a circular matrix;
training a classifier via a kernel method accelerated by faster Fourier transform in the west (FFTW);
obtaining tracking points using a sparse optical flow;
detecting object matching responses using a detection response function, wherein a location with a maximum response is a new location of the object;
performing multi-scale analysis for the object based on an optical flow method;
and
processing a next image frame of the plurality of image frames in the video until the video ends.

8 more elements

A high-speed automatic multi-object tracking system with kernelized correlation filters, comprising:

a video capture module configured to capture a video;
an obtaining module configured to obtain an image frame from a plurality of image frames in the video captured by the video capture module;
an extraction module configured to extract a foreground object sequence from the obtained image frame;
an image analyzer configured to:
determine similarity between each foreground object of the extracted foreground object sequence and a tracked object;
obtain training samples for each of the foreground objects with the lower similarity using a circular matrix;
train a classifier via a kernel method accelerated by faster Fourier transform in the west (FFTW);
and
obtain tracking points using a sparse optical flow;
and
a detection module configured to detect object matching responses using a detection response function and perform multi-scale analysis for the object based on an optical flow method, wherein a location with a maximum response is a new location of the object.

8 more elements

Dependencies are inferred from the claim text.

High-speed automatic multi-object tracking method and system with kernelized correlation filters

Life of this patent

High-speed automatic multi-object tracking method and system with kernelized correlation filters

Life of this patent

Abstract

Claims10