CN104933732A - Method for detecting and tracking movement target based on omnidirectional vision of robot - Google Patents
Method for detecting and tracking movement target based on omnidirectional vision of robot Download PDFInfo
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- CN104933732A CN104933732A CN201510249165.7A CN201510249165A CN104933732A CN 104933732 A CN104933732 A CN 104933732A CN 201510249165 A CN201510249165 A CN 201510249165A CN 104933732 A CN104933732 A CN 104933732A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
- G06T7/251—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments involving models
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
- G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/32—Indexing scheme for image data processing or generation, in general involving image mosaicing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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Abstract
A method for detecting and tracking a movement target based on omnidirectional vision of a robot relates to the technical field of robots. The method comprises the following steps: step 1: acquiring and analyzing an image; step 2: detecting the movement target: (2.1), detecting the movement target by adopting an inter-frame differential method, and analyzing an image sequence through an optical flow method after detection; (2.2), comparing two types of detection images in the step (2.1) to obtain incomplete data; (2.3), constructing the incomplete data into complete data by adopting a Gaussian mixture model; detecting the movement target through the Gaussian mixture model; and step 3: tracking the movement target: (3.1), establishing a target reference object, and carrying out target tracking and detection through the reference object, and filtering target color; and (3.2), carrying out positioning processing on the tracked target, and calculating the sequence of a positioned target. By virtue of the method, the target can be conveniently and quickly detected and tracked; and the positioning is accurate and convenient, the efficiency is improved and the safety is high.
Description
Technical field:
The present invention relates to robotics, be specifically related to a kind of method based on robot omnibearing visual movement target detection and tracking.
Background technology:
The information of objective world 70% is that the mankind are obtained by visually-perceptible organ eyes, and this visual information mankind obtain mainly through the message form of image.Current computer vision technique mainly obtains environmental information by traditional vision sensor, but the field range of traditional vision sensor is little, field angle is mostly within the scope of 50 °, the local message obtained is limited, cause system blind area larger, limit the range of application of computer vision, omnibearing vision sensor is because of the image 360 ° in the horizontal direction of disposable acquisition, the advantage of the scene image within the scope of vertical direction 120 °, become worldwide study hotspot in recent years, omni-directional visual technology is at safety monitoring, pipeline detection, field monitoring, vehicle-mountedly to patrol and examine, there is direct or potential application prospect the aspect such as aircraft guidance and robot for space.Especially fully-directional visual system has important application in anti-terrorism panzer.Adopt the target around omni-directional visual sensory perceptual system observation panzer, realize the detection and tracking to moving target.
Motion target tracking technology is the core of computer vision system, it is a fused images process, Model Identification, artificial intelligence, the hi-tech of the different field advanced achievements such as automatic control, it is one of gordian technique realizing intelligent robot and smart weapon, in military affairs, space flight, monitoring, the multiple fields such as biomedicine and Robotics are all widely used, video monitoring is the study hotspot of computer vision always, moving object detection in supervisory system and tracking are the most important things, next step process just can be done after target being detected, then the image collected by omnibearing vision sensor carries out the detection and tracking of moving target, to be promoted widely.
In video monitoring system, because obtaining the equipment of image sequence, being video camera mostly, whether moving according to it, detection two class of moving target under the detection and tracking of moving target are divided into static background and under dynamic background.
Because of the complicacy of target travel in environment, actual exist a lot of difficulty in the process of moving object detection and tracking, such as, whether target trajectory is complicated, whether target has change of shape, whether the color of background is close with color of object, in background, whether object exists motion, whether light change is strong, whether whether shade block between shield movement target and target mutually, whether clarification of objective is easily chosen, and these are all by difficulty that the detection and tracking being many Moving Object in Video Sequences bring.
Summary of the invention:
The object of this invention is to provide a kind of method based on robot omnibearing visual movement target detection and tracking, it is convenient to carry out detection and tracking to target fast, and accurate positioning, convenience, raise the efficiency, and security is high.
In order to solve the problem existing for background technology, the present invention adopts following technical scheme: its method is:
Step one: the gather and analysis of image:
(1.1), adopt camera to carry out collection image, after the figure of collection is carried out picture mosaic, obtain omnidirectional images;
(1.2), to omnidirectional images carry out performance analysis, adopt optical imaging concept to analyze; After analyzing, whether detected image is complete;
(1.3), to omnidirectional images carry out acoustic sounding, and form audio graphics;
Step 2: the detection of moving target:
(2.1), adopt frame differential method to carry out the detection of moving target, analyzed by the sequence of optical flow method to image after detection;
(2.2), by two kinds in above-mentioned (2.1) detect picture to contrast, contrast deficiency of data;
(2.3), adopt mixed Gauss model that deficiency of data is built into partial data; And carry out moving object detection by mixed Gauss model;
Step 3: the tracking of moving target:
(3.1), set up target object of reference, carry out target following detection by referring to thing, and color of object is filtered;
(3.2), to the target of following the tracks of position process, calculate the sequence of localizing objects.
The present invention has following beneficial effect: be convenient to carry out detection and tracking to target fast, accurate positioning, convenience, raise the efficiency, and security is high.
Embodiment:
This embodiment adopts following technical scheme: its method is:
Step one: the gather and analysis of image:
(1.1), adopt camera to carry out collection image, after the figure of collection is carried out picture mosaic, obtain omnidirectional images;
(1.2), to omnidirectional images carry out performance analysis, adopt optical imaging concept to analyze; After analyzing, whether detected image is complete;
(1.3), to omnidirectional images carry out acoustic sounding, and form audio graphics;
Step 2: the detection of moving target:
(2.1), adopt frame differential method to carry out the detection of moving target, analyzed by the sequence of optical flow method to image after detection;
(2.2), by two kinds in above-mentioned (2.1) detect picture to contrast, contrast deficiency of data;
(2.3), adopt mixed Gauss model that deficiency of data is built into partial data; And carry out moving object detection by mixed Gauss model;
Step 3: the tracking of moving target:
(3.1), set up target object of reference, carry out target following detection by referring to thing, and color of object is filtered;
(3.2), to the target of following the tracks of position process, calculate the sequence of localizing objects.
The above, be only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, and any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (1)
1., based on the method for robot omnibearing visual movement target detection and tracking, it is characterized in that its method is:
Step one: the gather and analysis of image:
(1.1), adopt camera to carry out collection image, after the figure of collection is carried out picture mosaic, obtain omnidirectional images;
(1.2), to omnidirectional images carry out performance analysis, adopt optical imaging concept to analyze; After analyzing, whether detected image is complete;
(1.3), to omnidirectional images carry out acoustic sounding, and form audio graphics;
Step 2: the detection of moving target:
(2.1), adopt frame differential method to carry out the detection of moving target, analyzed by the sequence of optical flow method to image after detection;
(2.2), by two kinds in above-mentioned (2.1) detect picture to contrast, contrast deficiency of data;
(2.3), adopt mixed Gauss model that deficiency of data is built into partial data; And carry out moving object detection by mixed Gauss model;
Step 3: the tracking of moving target:
(3.1), set up target object of reference, carry out target following detection by referring to thing, and color of object is filtered;
(3.2), to the target of following the tracks of position process, calculate the sequence of localizing objects.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510249165.7A CN104933732A (en) | 2015-05-15 | 2015-05-15 | Method for detecting and tracking movement target based on omnidirectional vision of robot |
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| CN201510249165.7A CN104933732A (en) | 2015-05-15 | 2015-05-15 | Method for detecting and tracking movement target based on omnidirectional vision of robot |
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| CN104933732A true CN104933732A (en) | 2015-09-23 |
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| CN201510249165.7A Pending CN104933732A (en) | 2015-05-15 | 2015-05-15 | Method for detecting and tracking movement target based on omnidirectional vision of robot |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528794A (en) * | 2016-01-15 | 2016-04-27 | 上海应用技术学院 | Moving object detection method based on Gaussian mixture model and superpixel segmentation |
| CN107038713A (en) * | 2017-04-12 | 2017-08-11 | 南京航空航天大学 | A kind of moving target method for catching for merging optical flow method and neutral net |
| CN111951558A (en) * | 2020-08-21 | 2020-11-17 | 齐鲁工业大学 | Machine vision system and method applied to traffic early warning robot |
-
2015
- 2015-05-15 CN CN201510249165.7A patent/CN104933732A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528794A (en) * | 2016-01-15 | 2016-04-27 | 上海应用技术学院 | Moving object detection method based on Gaussian mixture model and superpixel segmentation |
| CN105528794B (en) * | 2016-01-15 | 2019-01-25 | 上海应用技术学院 | Moving target detecting method based on mixed Gauss model and super-pixel segmentation |
| CN107038713A (en) * | 2017-04-12 | 2017-08-11 | 南京航空航天大学 | A kind of moving target method for catching for merging optical flow method and neutral net |
| CN111951558A (en) * | 2020-08-21 | 2020-11-17 | 齐鲁工业大学 | Machine vision system and method applied to traffic early warning robot |
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Application publication date: 20150923 |
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