WO2016008430A1 - 一种人体检测方法、装置和空调 - Google Patents

一种人体检测方法、装置和空调 Download PDF

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WO2016008430A1
WO2016008430A1 PCT/CN2015/084243 CN2015084243W WO2016008430A1 WO 2016008430 A1 WO2016008430 A1 WO 2016008430A1 CN 2015084243 W CN2015084243 W CN 2015084243W WO 2016008430 A1 WO2016008430 A1 WO 2016008430A1
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temperature
indoor
pixels
current
current time
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PCT/CN2015/084243
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English (en)
French (fr)
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毛跃辉
陶梦春
王子
梁博
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珠海格力电器股份有限公司
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Publication of WO2016008430A1 publication Critical patent/WO2016008430A1/zh

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00

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  • the invention belongs to the technical field of intelligent control and detection of electrical equipment, and particularly relates to a human body detecting method, device and air conditioner.
  • the indoor temperature and humidity can be adjusted to the optimal state when the indoors are detected, and the indoors are detected for a long time.
  • you turn off your own you can realize intelligent power-saving smart air conditioner.
  • smart air conditioners mostly use infrared human body sensors to sense and detect the presence of indoor human bodies, and perform corresponding intelligent control based on the detection results.
  • the infrared human body sensor detects the presence of the human body by detecting the infrared rays emitted by the human body, but the penetrating power of the human body infrared rays is poor, and is easily blocked by various objects, thereby affecting the sensitivity of the sensor to the human body, and the sensitivity of the infrared human body sensor to the human body. It also has a great relationship with people's movement direction. For example, it is the least sensitive to radial movement reaction.
  • the human body infrared sensor is susceptible to interference from various heat sources, light sources and radio frequency radiation, which ultimately leads to the detection accuracy of infrared human body sensors. Lower, it has a negative impact on the intelligent control of air conditioning.
  • the object of the present invention is to provide a human body detecting method, device and air conditioner to improve the accuracy of human body detection, thereby facilitating the intelligent control of the smart device.
  • the present invention provides a human body detecting method, including:
  • a candidate body having an area not less than the preset number of pixels is determined as a human body.
  • the obtaining the indoor temperature field data of the current time, and processing the indoor temperature field data of the current time to obtain the indoor current temperature including:
  • the current time average temperature value of the 8 ⁇ 8 pixel is linearly interpolated to obtain current time temperature data of 15 ⁇ 15 pixels, and the current time temperature data of the 15 ⁇ 15 pixels is used as the indoor current temperature.
  • the above method preferably, before the calculating the area of each candidate body, further comprises:
  • the candidate body For each candidate body, the candidate body is tracked according to the center of gravity of the candidate body, and the candidate body whose tracking result is the active heat source is substituted for the original candidate body as a new candidate body.
  • the area of the candidate body is the area of the minimum circumscribed rectangle of the candidate body, and the center of gravity of the candidate body is the geometric center of the minimum circumscribed rectangle of the candidate body.
  • the above method preferably, further includes:
  • the indoor background temperature is updated.
  • the updating the indoor background temperature comprises:
  • the background temperature of the unmanned pixels is updated based on the background temperature of the unmanned pixels and the current temperature distribution different weights.
  • a human body detecting device including a current temperature acquiring module, a differential processing module, A clustering module, a calculation module, and a decision module, wherein:
  • the current temperature acquisition module is configured to acquire indoor temperature field data of the current time, and process the indoor temperature field data of the current time to obtain an indoor current temperature, where the indoor current temperature is a preset size pixel matrix. a collection of temperatures at a point in time;
  • the difference processing module is configured to perform differential processing on the current temperature of the indoor and the indoor background temperature corresponding thereto to obtain a differential temperature of each pixel, where the indoor background temperature is a pixel in the pixel matrix. a set of temperatures at a certain time before the current time;
  • the clustering module is configured to cluster each pixel point whose differential temperature is not less than a preset threshold, obtain N heat sources, and use the N heat sources as N candidate bodies, and the heat source is obtained by clustering Cluster, the N is a natural number;
  • the calculation module is configured to calculate an area of each candidate body
  • the determining module is configured to determine a candidate body whose area is not less than the preset number of pixels as a human body.
  • the current temperature acquisition module comprises:
  • An obtaining unit configured to acquire indoor temperature data of a current time of 4 frames and 8 ⁇ 8 pixels
  • the mean value calculation unit is configured to calculate the moving average value of the temperature of each pixel at the current time by using the acquired indoor temperature data of the current frame of 4 frames, and obtain an average temperature value of the current time of 8 ⁇ 8 pixels;
  • an interpolation unit configured to linearly interpolate the current time average temperature value of the 8 ⁇ 8 pixels to obtain current time temperature data of 15 ⁇ 15 pixels, and use the current time temperature data of the 15 ⁇ 15 pixels as the indoor current temperature.
  • the above device preferably, further includes a tracking module connected to the clustering module and the computing module, the tracking module comprising:
  • a center of gravity calculation unit for calculating the center of gravity of each candidate body
  • the tracking unit is configured to track the candidate body according to the center of gravity of the candidate body for each candidate body, and replace the original candidate body with the candidate body whose tracking result is the active heat source as a new candidate body.
  • the above apparatus preferably, further includes a background update module, wherein the background update module is configured to update the indoor background temperature.
  • an air conditioner including an intelligent control device and a human body detecting device as described above, wherein the intelligent control device is configured to perform corresponding control on the indoor environment according to the detection result of the human body detecting device.
  • the present invention provides a human body detecting method, device and air conditioner.
  • the method is based on the fact that the body temperature and the indoor background temperature have a significant temperature difference, and the human body is detected by using the temperature change of each area in the room, that is, specifically
  • the method obtains the indoor temperature field data of the current time, and uses the processed current time temperature field data as the indoor current temperature, wherein the indoor current temperature is the current temperature set of each pixel point in the pixel matrix corresponding to the temperature place;
  • the difference between the indoor temperature and the corresponding indoor background temperature is performed, and the current temperature and the background temperature of each pixel are separately calculated to obtain the differential temperature of each pixel, and each of the differential temperatures is not less than a preset threshold.
  • the pixels are clustered to obtain N heat sources, and finally the heat source not less than the preset number of pixels is determined as the human body.
  • the invention realizes the human body detection by utilizing the temperature change of each area in the room, overcomes various shortcomings of the existing infrared detection mode, improves the detection accuracy, and brings greater convenience for the intelligent control of the smart device.
  • Embodiment 1 is a flow chart of a human body detecting method disclosed in Embodiment 1 of the present invention.
  • Embodiment 2 is another flow chart of a human body detecting method disclosed in Embodiment 2 of the present invention.
  • Embodiment 3 is still another flowchart of a human body detecting method disclosed in Embodiment 3 of the present invention.
  • Embodiment 4 is a schematic structural view of a human body detecting device disclosed in Embodiment 4 of the present invention.
  • FIG. 5 is another schematic structural diagram of a human body detecting apparatus according to Embodiment 4 of the present invention.
  • FIG. 6 is a schematic structural view of still another embodiment of a human body detecting device according to Embodiment 4 of the present invention.
  • FIG. 7 is a schematic structural view of an air conditioner according to Embodiment 5 of the present invention.
  • a first embodiment of the present invention discloses a human body detecting method. Referring to FIG. 1, the method includes the following steps:
  • S1 acquiring indoor temperature field data of the current time, and processing the indoor temperature field data of the current time to obtain an indoor temperature, where the current temperature of the indoor is the temperature of each pixel in the preset size pixel matrix at the current time. Collection.
  • the method of the present invention performs human body detection based on the temperature variation of each region in the room based on this feature.
  • thermopile sensor is used to detect the temperature of each area in the room, and the indoor temperature field data is obtained.
  • the thermopile sensor is a matrix sensor of 8 ⁇ 8, so that the obtained indoor temperature field data is 8 ⁇ 8 or 64 pixels of temperature data.
  • This step S1 specifically includes:
  • the temperature data of 4 frames of 8 ⁇ 8 pixels detected by the thermopile sensor at the current time is obtained, and the 12-bit temperature data obtained from the sensor is converted into computer-readable hexadecimal 16-bit temperature data for storage;
  • the moving average value of the saved 4 frames of data is calculated to obtain the current average temperature data of 8 ⁇ 8 pixels; and the current average temperature data of 8 ⁇ 8 pixels is linearly interpolated to expand the current temperature data of 15 ⁇ 15 pixels, and finally The current data of 15x15 pixels is used as the indoor temperature now.
  • linear data is used to process the acquired temperature data, and the temperature data of 8 ⁇ 8 pixels is expanded to the temperature data of 15 ⁇ 15 pixels, which is intended to improve the calculation accuracy of the subsequent calculation based on the temperature data, and the more the pixels, the more accurate the calculation. High, the accuracy of subsequent human detection using the differential temperature of each pixel is higher.
  • the current indoor temperature field data is acquired in advance at the start of the measurement (that is, at a certain time before the current time), specifically, the 8 frames detected by the thermopile sensor at the time are acquired.
  • 8x8 pixel temperature data and the moving average of the 8 frame temperature data is calculated to obtain average temperature data of 8x8 pixels; after that, the 8x8 pixel average temperature data is linearly interpolated and then expanded to 15x15 pixel temperature data.
  • the temperature data of 15x15 pixels is set as the indoor background temperature.
  • step S2 the indoor indoor temperature of 15 ⁇ 15 pixels and the indoor background temperature of 15 ⁇ 15 pixels obtained after the interpolation are subjected to differential processing to obtain a differential temperature of 15 ⁇ 15 pixels.
  • preliminary detection is performed, and the difference between the current temperature and the background temperature is determined at 0.5 ° C (can be set by the technician), and the pixel identification is determined as a heat source pixel, and the detected heat source pixel is marked. .
  • heat source pixels may belong to the same heat source (for example, the pixel A and the pixel B are both heat sources of the human body), based on this, the heat source division of each of the marked heat source pixels is required to obtain different heat sources. Subsequent human detection provides a basis, and this embodiment specifically uses clustering to achieve this purpose.
  • Clustering refers to the process of dividing a collection of physical or abstract objects into multiple clusters.
  • the cluster generated by clustering is a collection of data objects that are similar to each other in the same cluster. The objects are different.
  • the relative position of the heat source pixel is used as a basis for determining whether the heat source pixel is similar.
  • the heat source pixel located at 8 adjacent positions in the vicinity is regarded as the heat source pixel.
  • Similar pixels, and the similar pixel points and the heat source pixels are divided into the same heat source (ie, cluster) until the marked heat source pixels are divided.
  • the minimum circumscribed rectangle of each heat source that is, the candidate body
  • the area of the minimum circumscribed rectangle is approximated as the area of the candidate body.
  • S5 The candidate body whose area is not less than the preset number of pixels is determined as a human body.
  • the threshold number of pixels used for performing the human body determination can be set by a person skilled in the art according to actual needs.
  • a candidate body having an area greater than or equal to 10 pixels is specifically detected as a human body.
  • the present invention provides a human body detecting method, device and air conditioner.
  • the method is based on the fact that the body temperature and the indoor background temperature have a significant temperature difference, and the human body is detected by using temperature changes in various areas of the room, that is, specifically
  • the method obtains the indoor temperature field data of the current time, and uses the processed current time temperature field data as the indoor current temperature, wherein the indoor current temperature is a set of current temperature of each pixel point in the pixel matrix corresponding to the temperature place;
  • the temperature and its corresponding indoor background temperature are differentially processed, and the difference between the current temperature and the background temperature of each pixel is calculated to obtain the differential temperature of each pixel, and each pixel point whose differential temperature is not less than a preset threshold is obtained.
  • Clustering is performed to obtain N heat sources, and finally a heat source having an area not less than the preset number of pixels is determined as a human body.
  • the invention realizes the human body detection by utilizing the temperature change of each area in the room, overcomes various shortcomings of the existing infrared detection mode, improves the detection accuracy, and brings greater convenience for the intelligent control of the smart device.
  • the second embodiment continues to improve the human body detection method disclosed in the first embodiment.
  • the method further includes:
  • the geometric center of the minimum circumscribed rectangle of the candidate body is taken as the center of gravity of the candidate body.
  • the second embodiment increases the tracking link of the heat source, and uses the center of gravity of the heat source to track and detect the heat source, that is, specifically, whether the center of gravity of the same candidate body moves at the adjacent detection time, The candidate body that has moved is judged as the activity heat source, and finally the activity heat source is selected as the latest candidate body, which reduces the false detection rate.
  • the third embodiment continues to expand the human body detection method disclosed in the above embodiment.
  • the method further includes:
  • the background temperature needs to be updated.
  • the background temperature currently used is updated every time the human body is detected.
  • the background temperature of the pixel is updated based on the differential temperature of the unmanned pixel.
  • the background temperature (the background temperature at which the human body is currently detected) and the average differential temperature are summed, and the obtained temperature value is summed as the new background temperature of the human pixel.
  • the background temperature of the unmanned pixel is updated based on the background temperature of the unmanned pixel and the current temperature distribution different weights.
  • I BJUpdate (x,y) (1-a u )I BJ (x,y)+a u I Now (x,y)
  • x and y are the abscissa value and the ordinate value of the pixel point X, respectively, and are used to indicate the position of the pixel point X in the pixel matrix, and the values of x and y are specifically pixel points X, respectively.
  • I BJUpdate (x, y) represents the new background temperature of pixel X
  • I BJ (x, y) represents the background temperature of the pixel point X (the background temperature currently used by the human body is detected);
  • I Now (x, y) represents the current temperature of the pixel point X (ie, the temperature at which the human body is currently detected);
  • a u is an update weight coefficient of the background temperature, and the coefficient can be set by a person skilled in the art according to actual needs.
  • a u 0.02.
  • the new background temperature of all unmanned and human pixels is integrated, and the new background temperature of all pixels is connected according to the relative position of each pixel in the pixel matrix. Get up and get a new background temperature of 15x15 pixels.
  • the fourth embodiment discloses a human body detecting device, which corresponds to the human body detecting method disclosed in the above embodiments.
  • this embodiment first discloses a structure of the above device. Referring to FIG. 4, the current temperature acquisition module 101, the difference processing module 102, the clustering module 103, and the calculation module 104 are included. And decision module 105.
  • the temperature acquisition module 101 is configured to acquire indoor temperature field data of the current time, and process the indoor temperature field data of the current time to obtain an indoor temperature, where the indoor temperature is a pixel in a preset size pixel matrix. Point the set of temperatures at the current moment.
  • the current temperature acquisition module 102 includes an acquisition unit, an average calculation unit, and an interpolation unit.
  • An obtaining unit configured to acquire indoor temperature data of a current time of 4 frames and 8 ⁇ 8 pixels
  • the mean value calculation unit is configured to calculate the moving average value of the temperature of each pixel at the current time by using the acquired indoor temperature data of the current frame of 4 frames, and obtain an average temperature value of the current time of 8 ⁇ 8 pixels;
  • an interpolation unit configured to linearly interpolate the current time average temperature value of the 8 ⁇ 8 pixels to obtain current time temperature data of 15 ⁇ 15 pixels, and use the current time temperature data of the 15 ⁇ 15 pixels as the indoor current temperature.
  • the difference processing module 102 is configured to perform differential processing on the indoor temperature and the corresponding indoor background temperature to obtain a differential temperature of each pixel, where the indoor background temperature is the pixel in the pixel matrix. A collection of temperatures at a certain moment before the current moment.
  • the clustering module 103 is configured to cluster each pixel point whose differential temperature is not less than a preset threshold, obtain N heat sources, and use the N heat sources as N candidate bodies, and the heat source is obtained by performing clustering.
  • Cluster the N is a natural number.
  • the calculation module 104 is configured to calculate the area of each candidate body.
  • the determining module 105 is configured to determine a candidate body whose area is not less than the preset number of pixels as a human body.
  • the device further includes a tracking module 106 connected to the clustering module 103 and the computing module 104.
  • the tracking module 106 includes a center of gravity calculating unit and a tracking unit.
  • a center of gravity calculation unit for calculating the center of gravity of each candidate body
  • a tracking unit configured to track the candidate body according to the center of gravity of the candidate body for each candidate body, and replace the original candidate body with the candidate body whose tracking result is the active heat source For the new candidate body.
  • the device further includes a background update module 107, which is used to update the indoor background temperature.
  • the description is relatively simple.
  • This embodiment discloses an air conditioner.
  • the intelligent control device 200 and the human body detecting device 100 disclosed in the fourth embodiment are provided.
  • the intelligent control device 200 is configured to perform corresponding control on the indoor environment according to the detection result of the human body detecting device 100. .
  • the intelligent control device 200 adjusts the indoor temperature and humidity to an optimal state according to the amount of human activity, so that the human body senses more comfortably; when the indoor time is unmanned, the intelligent control device 200 control air conditioner shutdown, to achieve intelligent power saving.
  • the present invention realizes the accurate detection of the temperature field in the indoor area through the matrix thermopile sensor, and realizes the detection of the human activity on the basis of the invention, thereby improving the accuracy of the human body detection, and further intelligent control of the intelligent device. Bring more convenience.
  • the present application can be implemented by means of software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be in the form of a software product.
  • the computer software product can be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, a network device, etc.) to execute.
  • a computer device which can be a personal computer, a server, a network device, etc.

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Abstract

一种人体检测方法、装置和空调，该方法基于人体体温与室内背景温度有明显温差的特点，利用室内各区域的温度变化情况进行人体检测，包括：获取当前的室内温度场数据，并将处理后的当前室内温度场数据作为室内现在温度，其中，室内现在温度为温度场所对应的像素矩阵中各像素点当前温度的集合（S1）；之后对室内现在温度和与其对应的室内背景温度进行差分处理，得到各像素点的差分温度（S2），并对差分温度不小于预设阈值的各像素点进行聚类，得到Ｎ个热源（S3），最终将不小于预设像素个数的热源判定为人体（S5）。

Description

一种人体检测方法、装置和空调
本申请要求于2014年07月17日提交中国专利局、申请号为201410342467.4、发明名称为“一种人体检测方法、装置和空调”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明属于电器设备智能控制、检测技术领域，尤其涉及一种人体检测方法、装置和空调。
背景技术
随着科学技术的不断发展，自动化、智能化的电器产品成为当前的研究热门，例如，能够在检测到室内有人时将室内温度、湿度自行调节到最佳状态，在检测到室内长时间无人时自行关机，实现智能节电的智能空调等。
目前，智能空调多采用红外线人体传感器来感知、检测室内人体存在情况，并基于检测结果进行相应的智能控制。红外线人体传感器通过检测人体发射的红外线来感知人体是否存在，但人体红外线的穿透力较差，易被各种物体遮挡，从而影响了传感器对人体的敏感程度，红外线人体传感器对人体的敏感程度还和人的运动方向关系很大，例如，其对于径向移动反应最不敏感，同时，人体红外线传感器易受各种热源、光源、射频辐射的干扰，最终导致了红外线人体传感器的检测准确度较低，对空调的智能控制带来了不利影响。
可见，提供一种准确度较高的人体检测方法或装置成为本领域亟需解决的问题。
发明内容
有鉴于此，本发明的目的在于提供一种人体检测方法、装置和空调，以提高人体检测的准确度，进而为智能设备的智能控制带来便利。
为了解决以上技术问题，本发明提供一种人体检测方法，包括：
获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合；
对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合；
对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数；
计算每个候选人体的面积；
将面积不小于预设像素个数的候选人体判定为人体。
上述方法，优选的，所述获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，包括：
获取4帧8x8像素的当前时刻室内温度数据；
利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
上述方法，优选的，在所述计算每个候选人体的面积之前还包括：
计算各个候选人体的重心；
对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作为新的候选人体。
上述方法，优选的，所述候选人体的面积为所述候选人体的最小外接矩形的面积，所述候选人体的重心为所述候选人体的最小外接矩形的几何中心。
上述方法，优选的，还包括：
对所述室内背景温度进行更新。
上述方法，优选的，所述对所述室内背景温度进行更新包括：
基于无人像素的差分温度对有人像素的背景温度进行更新；
基于对无人像素的背景温度、现在温度分配不同权重对无人像素的背景温度进行更新。
同时，提供了一种人体检测装置，包括现在温度获取模块、差分处理模块、 聚类模块、计算模块和判定模块，其中：
所述现在温度获取模块，用于获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合；
所述差分处理模块，用于对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合；
所述聚类模块，用于对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数；
所述计算模块，用于计算每个候选人体的面积；
所述判定模块，用于将面积不小于预设像素个数的候选人体判定为人体。
上述装置，优选的，所述现在温度获取模块包括：
获取单元，用于获取4帧8x8像素的当前时刻室内温度数据；
均值计算单元，用于利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
插值单元，用于对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
上述装置，优选的，还包括与所述聚类模块和计算模块相连的跟踪模块，所述跟踪模块包括：
重心计算单元，用于计算各个候选人体的重心；
跟踪单元，用于对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作为新的候选人体。
上述装置，优选的，还包括背景更新模块，所述背景更新模块用于对所述室内背景温度进行更新。
在此基础上，还提供了一种空调，包括智能控制装置以及如上所述的人体检测装置，所述智能控制装置用于依据所述人体检测装置的检测结果对室内环境进行相应控制。
由以上方案可知，本发明提供一种人体检测方法、装置和空调，所述方法基于人体体温与室内背景温度有明显温差这一特点，利用室内各区域的温度变化情况进行人体检测，即具体地，所述方法获取当前时刻的室内温度场数据，并将处理后的当前时刻温度场数据作为室内现在温度，其中，室内现在温度为温度场所对应的像素矩阵中各像素点当前温度的集合；之后对室内现在温度和与其相对应的室内背景温度进行差分处理，具体对各像素点的现在温度和背景温度进行差分运算，得到各像素点的差分温度，并对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，最终将不小于预设像素个数的热源判定为人体。
可见，本发明利用室内各区域的温度变化情况实现了人体检测，克服了现有红外线检测方式的各种缺点，提高了检测的准确度，为智能设备的智能控制带来了更大便利。
附图说明
图1是本发明实施例一公开的人体检测方法的一种流程图；
图2是本发明实施例二公开的人体检测方法的另一种流程图；
图3是本发明实施例三公开的人体检测方法的又一种流程图；
图4是本发明实施例四公开的人体检测装置的一种结构示意图；
图5是本发明实施例四公开的人体检测装置的另一种结构示意图；
图6是本发明实施例四公开的人体检测装置的又一种结构示意图；
图7是本发明实施例五公开的空调结构示意图。
具体实施方式
为了进一步了解本发明，下面结合实施例对本发明优选实施方案进行描述，但是应当理解，这些描述只是为进一步说明本发明的特征和优点，而不是对本发明权利要求的限制。
实施例一
本发明实施例一公开一种人体检测方法，请参见图1，该方法包括如下步骤：
S1：获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合。
由于人体体温与室内背景温度有明显温差，本发明的方法基于这一特点利用室内各区域的温度变化情况进行人体检测。
其中，本实施例采用热电堆传感器来检测室内各区域的温度，获取室内温度场数据，热电堆传感器为8X8的矩阵式传感器，从而获取的室内温度场数据为8X8即64像素的温度数据。
本步骤S1具体包括：
1)获取4帧8x8像素的当前时刻室内温度数据；
2)利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
3)对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
例如，本实施例获取当前时刻由热电堆传感器检测的4帧8x8像素的温度数据，并将从传感器取得的12bit的该温度数据变换为计算机可读的十六进制的16bit温度数据进行保存；之后，对保存的4帧数据进行移动平均值的计算，得到8x8像素的当前平均温度数据；并通过对8x8像素的当前平均温度数据进行线性插值将其扩大为15x15像素的当前温度数据，最后将该15x15像素当前数据作为室内现在温度。
其中，本实施例采用线性插值对获取的温度数据进行处理，将8x8像素的温度数据扩大为15x15像素的温度数据，旨在提高后续基于温度数据进行相应计算的计算精度，像素越多计算精度越高，后续利用各像素的差分温度进行人体检测的准确度就越高。
S2：对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合。
其中，本实施例中，预先在测定开始时(即当前时刻之前的某一时刻)获取当时的室内温度场数据，具体地，获取当时由热电堆传感器检测的8帧的 8x8像素温度数据，并对该8帧温度数据进行移动平均值的计算，得到8x8像素的平均温度数据；之后，对该8x8像素的平均温度数据进行线性插值后将其扩大为15x15像素的温度数据，最后将该15x15像素的温度数据设定为室内背景温度。
本步骤S2对插值后所得的15x15像素的室内现在温度和15x15像素的室内背景温度进行差分处理，得到15x15像素的差分温度。
S3：对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数。
本步骤进行初步检测，将当前温度和背景温度的差分温度在0.5℃(可由技术人员自行设定)以上的像素点识别判定为热源像素点进行检出，并对检出的热源像素点进行标记。
由于某些热源像素点可能属于同一热源(例如，像素点A与像素点B同属人体这一热源)，基于此，需对标记出的各个热源像素点进行热源划分，以得到不同的热源，为后续的人体检测提供基础，本实施例具体采用聚类实现这一目的。
其中，聚类是指将物理或抽象对象的集合分成多个簇的过程，聚类所产生的簇是一组数据对象的集合，这些对象与同一个簇中的对象彼此相似，与其他簇中的对象相异。
本实施例以热源像素点的相对位置作为热源像素点是否相似的判定依据，具体地，针对标记出的热源像素点，将位于其附近8个相邻位置的热源像素点视为该热源像素点的相似像素点，并将相似像素点与该热源像素点划分至同一热源(即簇)，直至将标记出的各个热源像素点划分完毕为止。
S4：计算每个候选人体的面积。
求解每个热源即候选人体的最小外接矩形，并将所述最小外接矩形的面积(以其包括的像素个数进行衡量)近似作为候选人体的面积。
S5：将面积不小于预设像素个数的候选人体判定为人体。
其中，进行人体判定所采用的像素个数阈值可由本领域技术人员依据实际需求进行自行设定。本实施例具体将面积大于或等于10个像素的候选人体作为人体进行检出。
综上，本发明提供一种人体检测方法、装置和空调，所述方法基于人体体温与室内背景温度有明显温差这一特点，利用室内各区域的温度变化情况进行人体检测，即具体地，所述方法获取当前时刻的室内温度场数据，并将处理后的当前时刻温度场数据作为室内现在温度，其中，室内现在温度为温度场所对应的像素矩阵中各像素点当前温度的集合；之后对室内现在温度和其相对应的室内背景温度进行差分处理，具体对各像素点的现在温度和背景温度进行差分运算，得到各像素点的差分温度，并对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，最终将面积不小于预设像素个数的热源判定为人体。
可见，本发明利用室内各区域的温度变化情况实现了人体检测，克服了现有红外线检测方式的各种缺点，提高了检测的准确度，为智能设备的智能控制带来了更大便利。
实施例二
本实施例二继续对实施例一公开的人体检测方法进行改进，请参见图2，本实施例中，在步骤S4之前还包括：
S6：计算各个候选人体的重心；对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作为新的候选人体。
其中，本实施例将候选人体的最小外接矩形的几何中心作为候选人体的重心。
为进一步提高检测的准确度、精度，本实施例二增加对热源的跟踪环节，利用热源的重心对热源进行跟踪检测，即具体地，比较同一候选人体的重心在相邻检测时刻是否发生移动，并将发生移动的候选人体判定为活动热源，最后将活动热源筛选出来作为最新的候选人体，降低了误检率。
实施例三
本实施例三继续对以上实施例公开的人体检测方法进行拓展，请参见图3，本实施例中，该方法还包括：
S7：对所述室内背景温度进行更新。
现实应用场景中，由于室内人体存在情况会随时发生变化，从而往往会对 室内人体存在情况进行持续地、实时地监测，为保证背景温度的时效性，需对背景温度进行更新，本实施例具体在每次检测出人体存在时，对当前所采用的背景温度进行更新，具体更新过程如下：
1)基于无人像素的差分温度对有人像素的背景温度进行更新。
首先，计算15x15像素中所有无人像素的差分温度的平均值，得到无人像素的平均差分温度；
之后，针对每个有人像素，对其背景温度(当前检出人体所采用的背景温度)和所述平均差分温度进行求和运算，求和所得温度值作为该有人像素的新的背景温度。
2)基于对无人像素的背景温度、现在温度分配不同权重对无人像素的背景温度进行更新。
具体采用如下公式(1)实现无人像素背景温度的更新，得到无人像素的新的背景温度：
IBJUpdate(x,y)＝(1-au)IBJ(x,y)+auINow(x,y)
(1)
其中，式(1)中，x、y分别为像素点X的横坐标值、纵坐标值，用于表示像素点X在像素矩阵中的位置，x、y的取值具体分别为像素点X在像素矩阵中所处的列数、行数，在本实施例的15x15像素矩阵中，x、y的取值为1～15的15个自然数；
IBJUpdate(x,y)表示像素点X的新的背景温度；
IBJ(x,y)表示像素点X的背景温度(当前检出人体所采用的背景温度)；
INow(x,y)表示像素点X的现在温度(即当前检出人体时的温度)；
au为背景温度的更新权重系数，该系数可由本领域技术人员依据实际需求自行设定，本实施例中，au＝0.02。
当所有无人、有人像素的背景温度更新完毕之后，对所有无人及有人像素的新的背景温度进行整合，具体依据各像素点在像素矩阵中的相对位置将所有像素的新的背景温度衔接起来，得到一帧15x15像素的新的背景温度。
本实施例通过在每次检出人体存在时对当前所采用的背景温度进行更新，保证了人体检测过程中背景温度的时效性，进一步提高了人体检测的准确度。
实施例四
本实施例四公开一种人体检测装置，该装置与以上实施例公开的人体检测方法相对应。
相应于实施例一中人体检测方法的流程，本实施例首先公开上述装置的一种结构，请参见图4，其包括现在温度获取模块101、差分处理模块102、聚类模块103、计算模块104和判定模块105。
现在温度获取模块101，用于获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合。
其中，现在温度获取模块102包括获取单元、均值计算单元和插值单元。
获取单元，用于获取4帧8x8像素的当前时刻室内温度数据；
均值计算单元，用于利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
插值单元，用于对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
差分处理模块102，用于对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合。
聚类模块103，用于对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数。
计算模块104，用于计算每个候选人体的面积。
判定模块105，用于将面积不小于预设像素个数的候选人体判定为人体。
相应于实施例二中人体检测方法的流程，如图5所示，上述装置还包括与聚类模块103和计算模块104相连的跟踪模块106，跟踪模块106包括重心计算单元和跟踪单元。
重心计算单元，用于计算各个候选人体的重心；
跟踪单元，用于对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作 为新的候选人体。
相应于实施例三，如图6所示，上述装置还包括背景更新模块107，该模块用于对所述室内背景温度进行更新。
对于本发明实施例四公开的人体检测装置而言，由于其与以上各实施例公开的人体检测方法相对应，所以描述的比较简单，相关相似之处请参见以上各实施例中人体检测方法部分的说明即可，此处不再详述。
实施例五
本实施例公开一种空调，请参见图7，其包括智能控制装置200和实施例四公开的人体检测装置100，智能控制装置200用于依据人体检测装置100的检测结果对室内环境进行相应控制。
具体地，当人体检测装置100检测出室内有人存在时，智能控制装置200根据人体活动量将室内温度、湿度调节到最佳状态，使人体感知更加舒服；当室内长时间无人时智能控制装置200控制空调关机，实现智能节电。
综上所述，本发明通过矩阵热电堆传感器实现了室内区域温度场的精准检测，并在此基础上实现了人体活动量的检测，提高了人体检测的准确度，进而为智能设备的智能控制带来了更大便利。
需要说明的是，本申请所涉及到的具体数值，例如4帧、8帧、8x8像素、15x15像素等仅为实施本发明内容对相应参数所做的示例性说明，在应用本发明时，各参数的取值不必局限于本申请所提供的具体数值，在不脱离本申请精神或范围的前提下，本领域技术人员可依据实际需求进行自行设定。
还需要说明的是，本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。
为了描述的方便，描述以上装置时以功能分为各种模块或单元分别描述。当然，在实施本申请时可以把各模块、单元的功能在同一个或多个软件和/或硬件中实现。
通过以上的实施方式的描述可知，本领域的技术人员可以清楚地了解到本申请可借助软件加必需的通用硬件平台的方式来实现。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形 式体现出来，该计算机软件产品可以存储在存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例或者实施例的某些部分所述的方法。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (11)

  1. 一种人体检测方法，其特征在于，包括：
    获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合；
    对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合；
    对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数；
    计算每个候选人体的面积；
    将面积不小于预设像素个数的候选人体判定为人体。
  2. 根据权利要求1所述的方法，其特征在于，所述获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，包括：
    获取4帧8x8像素的当前时刻室内温度数据；
    利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
    对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
  3. 根据权利要求1所述的方法，其特征在于，在所述计算每个候选人体的面积之前还包括：
    计算各个候选人体的重心；
    对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作为新的候选人体。
  4. 根据权利要求3所述的方法，其特征在于，所述候选人体的面积为所 述候选人体的最小外接矩形的面积，所述候选人体的重心为所述候选人体的最小外接矩形的几何中心。
  5. 根据权利要求1所述的方法，其特征在于，还包括：
    对所述室内背景温度进行更新。
  6. 根据权利要求5所述的方法，其特征在于，所述对所述室内背景温度进行更新包括：
    基于无人像素的差分温度对有人像素的背景温度进行更新；
    基于对无人像素的背景温度、现在温度分配不同权重对无人像素的背景温度进行更新。
  7. 一种人体检测装置，其特征在于，包括现在温度获取模块、差分处理模块、聚类模块、计算模块和判定模块，其中：
    所述现在温度获取模块，用于获取当前时刻的室内温度场数据，并对所述当前时刻的室内温度场数据进行处理，得到室内现在温度，所述室内现在温度为预设大小像素矩阵中各像素点在当前时刻的温度的集合；
    所述差分处理模块，用于对所述室内现在温度以及与其相对应的室内背景温度进行差分处理，得到各像素点的差分温度，所述室内背景温度为所述像素矩阵中各像素点在所述当前时刻之前的某一时刻的温度的集合；
    所述聚类模块，用于对差分温度不小于预设阈值的各像素点进行聚类，得到N个热源，并将所述N个热源作为N个候选人体，所述热源为进行聚类所得的簇，所述N为自然数；
    所述计算模块，用于计算每个候选人体的面积；
    所述判定模块，用于将面积不小于预设像素个数的候选人体判定为人体。
  8. 根据权利要求7所述的装置，其特征在于，所述现在温度获取模块包括：
    获取单元，用于获取4帧8x8像素的当前时刻室内温度数据；
    均值计算单元，用于利用获取的4帧当前时刻室内温度数据，计算每个像素在当前时刻的温度的移动平均值，得到8x8像素的当前时刻平均温度值；
    插值单元，用于对所述8x8像素的当前时刻平均温度值进行线性插值，得到15x15像素的当前时刻温度数据，将所述15x15像素的当前时刻温度数据作为室内现在温度。
  9. 根据权利要求7所述的装置，其特征在于，还包括与所述聚类模块和计算模块相连的跟踪模块，所述跟踪模块包括：
    重心计算单元，用于计算各个候选人体的重心；
    跟踪单元，用于对于每个候选人体，依据所述候选人体的重心对所述候选人体进行跟踪，并将跟踪结果为活动热源的候选人体替代原有的候选人体，作为新的候选人体。
  10. 根据权利要求9所述的人体检测装置，其特征在于，还包括背景更新模块，所述背景更新模块用于对所述室内背景温度进行更新。
  11. 一种空调，其特征在于，包括智能控制装置以及如权利要求7-10任意一项所述的人体检测装置，所述智能控制装置用于依据所述人体检测装置的检测结果对室内环境进行相应控制。
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