CN111355932A - Monitoring method and device, household equipment, storage medium and electronic equipment - Google Patents
Monitoring method and device, household equipment, storage medium and electronic equipment Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
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Abstract
The invention relates to the technical field of household equipment, in particular to a monitoring method, a monitoring device, household equipment, a storage medium and electronic equipment.
Description
Technical Field
The invention relates to the technical field of household equipment, in particular to a monitoring method, a monitoring device, household equipment, a storage medium and electronic equipment.
Background
With the development of society and the improvement of living standard, the society is more stable in security, crime rate is gradually reduced, but illegal criminal events still occur at times, and especially for small and medium-sized service stores such as convenience stores and restaurants, people injury events caused by burglary or robbery threaten the security of lives and properties of people, so that how to guarantee the security of lives and properties of people becomes a problem to be solved urgently.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a monitoring method, a monitoring apparatus, a home device, a storage medium, and an electronic device.
In a first aspect, the present invention provides a monitoring method, including: acquiring a sound signal acquired by sound acquisition equipment;
when the received sound signal is a first preset sound signal, controlling the camera equipment to collect video information;
identifying a monitoring object in the video information;
judging whether a monitored object in the video information has a preset abnormal behavior or not;
and if the preset abnormal behavior exists in the monitored object in the video information, generating an abnormal behavior warning instruction.
Furthermore, the video information comprises a plurality of segments of sub-video information, and the time length of each segment of sub-video information is the same; the step of judging whether the monitoring object in the video information has a preset abnormal behavior includes:
and judging whether all the sub-video information contains the sub-video information of the monitored object with the preset abnormal behavior.
Further, if the preset abnormal behavior exists in the monitored object in the video information, the step of generating an abnormal behavior warning instruction includes:
if the monitored object has the sub-video information with the preset abnormal behavior in all the sub-video information, counting the number of segments of the sub-video information with the preset abnormal behavior in all the sub-video information;
judging whether the number of the sections is larger than a preset abnormal number of the sections;
and if the number of the sections is larger than the preset abnormal number of the sections, determining that the monitored object has abnormal behavior, and generating an abnormal behavior warning instruction.
Further, the step of determining whether there is sub video information of the preset abnormal behavior in all the sub video information of the monitored object includes:
acquiring multi-frame image information in each section of the sub-video information;
calculating the abnormal probability of each frame of image information in each section of sub-video information by using a preset convolutional neural network and the multi-frame image information in each section of sub-video information;
calculating the average value of the abnormal probability of all the image information in each section of the video information to obtain the average abnormal probability of each section of the video information;
and judging whether each average abnormal probability is larger than a preset abnormal probability.
Further, if there is sub video information of the preset abnormal behavior in the monitored object in all the sub video information, the step of counting the number of segments of the sub video information of the preset abnormal behavior in all the sub video information includes:
and if the average abnormal probability is greater than the preset abnormal probability, determining that abnormal behaviors exist in the section of sub-video information, and counting the number of the sections of the sub-video information with the preset abnormal behaviors in all the sub-video information.
Further, the method further comprises: and if the preset abnormal behavior exists in the video information, controlling the camera equipment to track a monitored object to acquire the video information.
Further, the method further comprises: acquiring a sound signal acquired by the sound acquisition equipment;
and when the received sound signal is a second preset sound signal, controlling the camera equipment to stop collecting the video information.
In a second aspect, the present invention further provides a monitoring apparatus, including:
the acquisition module is used for acquiring the sound signals acquired by the sound acquisition equipment;
the control module is used for controlling the camera equipment to collect video information when the received sound signal is a first preset sound signal;
the identification module is used for identifying a monitored object in the video information;
the judging module is used for judging whether a monitoring object in the video information has a preset abnormal behavior;
and the generating module is used for generating an abnormal behavior warning instruction when the preset abnormal behavior exists in the monitored object in the video information.
In a third aspect, the present invention further provides a home device, where the home device includes: the system comprises sound collection equipment, camera equipment and a processor, wherein the sound collection equipment and the camera equipment are electrically connected with the processor;
the sound acquisition equipment is used for acquiring sound signals and sending the sound signals to the processor;
the processor is used for controlling the camera equipment to collect video information when the received sound signal is a first preset sound signal;
the processor is further used for receiving the video information acquired by the camera equipment and identifying a monitoring object in the video information;
the processor is further configured to determine whether a preset abnormal behavior exists in a monitored object in the video information; and if the preset abnormal behavior exists in the monitored object in the video information, generating an abnormal behavior warning instruction.
In a fourth aspect, the present invention also provides a storage medium storing a computer program, where the storage medium, when executed by one or more processors, implements the monitoring method of the first aspect.
In a fifth aspect, the present invention further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program, and the computer program, when executed by the processor, performs the monitoring method according to the first aspect.
The monitoring method, the monitoring device, the household equipment, the storage medium and the electronic equipment provided by the invention are used for acquiring the sound signal acquired by the sound acquisition equipment, controlling the camera equipment to work when the received sound signal is the first preset sound signal, acquiring the video information, identifying the monitored object in the video information, judging whether the monitored object has preset abnormal behaviors or not, and generating an abnormal behavior warning instruction to warn the monitored object if the monitored object has the preset abnormal behaviors, so that the life and property safety of a user is ensured.
Drawings
The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings:
fig. 1 is a schematic diagram of a home device connection provided in an embodiment of the present invention;
fig. 2 is a schematic flow chart of a monitoring method according to an embodiment of the present invention;
fig. 3 is another schematic flow chart of a monitoring method according to an embodiment of the present invention;
fig. 4 is another schematic flow chart of a monitoring method according to an embodiment of the present invention;
fig. 5 is another schematic flow chart of a monitoring method according to an embodiment of the present invention;
fig. 6 is a connection block diagram of a monitoring device according to an embodiment of the present invention.
Reference numerals: 1-household equipment; 11-a sound collection device; 12-a processor; 13-an image pickup apparatus; 2-a monitoring device; 21-an acquisition module; 22-a control module; 23-an identification module; 24-a judgment module; 25-generating module.
In the drawings, like parts are designated with like reference numerals, and the drawings are not drawn to scale.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the accompanying drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the corresponding technical effects can be fully understood and implemented. The embodiments of the present invention and the features of the embodiments can be combined with each other without conflict, and the formed technical solutions are within the scope of the present invention.
Example one
In order to solve the above problems in the prior art, this embodiment provides a home device, and specifically, fig. 1 is a schematic connection diagram of a home device provided in an embodiment of the present invention, please refer to fig. 1, where the home device 1 includes: the system comprises a sound collection device 11, an image pickup device 13 and a processor 12, wherein the sound collection device 11 and the image pickup device 13 are electrically connected with the processor 12;
and the sound collecting device 11 is used for collecting sound signals and sending the sound signals to the processor 12.
Alternatively, the sound collection device 11 may be, but is not limited to, a sound pickup.
And the processor 12 is used for controlling the camera device 13 to collect video information when the received sound signal is a first preset sound signal.
Alternatively, the camera device 13 may be, but is not limited to, a color camera, an infrared camera, an auto-tracking camera, and the like.
And the processor 12 is further configured to receive video information acquired by the image pickup device 13, and identify a monitored object in the video information.
The processor 12 is further configured to determine whether a preset abnormal behavior exists in the monitored object in the video information; and if the monitored object in the video information has preset abnormal behavior, generating an abnormal behavior warning instruction.
Optionally, the household device 1 may be an air conditioner, for example, a hanging air conditioner, generally speaking, the hanging air conditioner is installed at a higher position in a room, and the camera device 13 thereon may collect image information of each place in the room, so as to reduce a dead zone of camera shooting.
It should be noted that the home equipment may be, besides an air conditioner, a refrigerator, a television, a desktop computer, and other home equipment.
Fig. 2 is a schematic flow chart of a monitoring method according to an embodiment of the present invention, and it should be noted that the monitoring method according to the embodiment of the present invention is not limited by fig. 2 and the following specific sequence, and it should be understood that, in other embodiments, the sequence of some steps in the monitoring method according to the embodiment of the present invention may be interchanged according to actual needs, or some steps in the monitoring method may be omitted or deleted. This process may be performed by the corresponding processor 12 of fig. 1, and the specific process referred to in fig. 2 will be described below, as shown in fig. 2, the method includes:
and step S1, acquiring the sound signal collected by the sound collection device.
The sound collection equipment collects indoor sound signals in real time and sends the collected sound signals to the processor. The sound signal may be the dialogue content or the decibel of the sound.
And step S2, controlling the camera device to collect the video information when the received sound signal is the first preset sound signal.
When the voice signal is the conversation content, the first preset voice signal may be "lifesaving" or "o", etc.; when the sound signal is a decibel of sound, the first predetermined sound signal may be 70 decibels, 75 decibels, etc.
And step S3, identifying the monitored object in the video information.
And step S4, judging whether the monitored object in the video information has a preset abnormal behavior.
Alternatively, the abnormal behavior may be burglary, robbery, or the like.
If the monitored object in the video information has a preset abnormal behavior, the flow goes to step S5; if the monitored object in the video information has no preset abnormal behavior, the process goes to step S6.
Step S5, an abnormal behavior warning command is generated.
Optionally, the warning instruction may be an instruction for controlling the buzzer to send out an alarm signal, an instruction for controlling the display device to play video information, and an instruction for controlling the communication device to make an alarm call.
And step S7, controlling the camera device to track the monitored object and acquire video information.
And step S6, controlling the camera equipment to continue to collect the video information.
In the monitoring method provided by this embodiment, a sound collection device collects an indoor sound signal in real time, when the collected sound signal is a first preset sound signal, an indoor abnormal behavior may occur, a processor controls a camera device to operate, the camera device collects indoor video information, the processor identifies a monitored object in the video information, determines whether the monitored object has an abnormal behavior, generates an abnormal behavior warning instruction if the monitored object has an abnormal behavior, controls the camera device to track the monitored object to collect the video information, and controls the camera device to continue to collect the video information if the monitored object does not have an abnormal behavior. If the camera device collects the video information in real time, the memory occupied by the collected video information is large, and the collected video information is not beneficial to protecting the privacy of the user when the user works and lives normally; when the monitoring object has abnormal behaviors, an abnormal behavior warning instruction is generated, and the life and property safety of the user is ensured.
Example two
On the basis of the foregoing embodiment, the present embodiment provides a monitoring method, which completes indoor monitoring by determining whether there is an abnormal line in multiple segments of sub-video information, specifically, the video information includes multiple segments of sub-video information, and the duration of each segment of sub-video information is the same, for example, the duration of each segment of sub-video information is 2 minutes, fig. 3 is another flow diagram of the monitoring method provided in the embodiment of the present invention, please refer to fig. 3, and step S4 includes:
and a substep S41 of judging whether all the sub-video information contains the sub-video information of the monitored object with the preset abnormal behavior.
If the monitored object has the sub video information with the preset abnormal behavior in all the sub video information, the process goes to step S51; if there is no sub-video information with a preset abnormal behavior in the monitoring object in all the sub-video information, the process proceeds to step S6.
Step S5 includes the following sub-steps:
and a substep S51, counting the number of segments of the sub video information with preset abnormal behaviors in all the sub video information.
And a substep S52 of judging whether the segment number is larger than the preset abnormal segment number.
If the number of segments is greater than the preset abnormal number of segments, the process goes to step S53, for example, if the number of segments of the sub video information with the preset abnormal behavior is 5 segments, the number of segments of the sub video information with the preset abnormal behavior is 4 segments, and the preset abnormal number of segments is 3 segments, the number of segments 4 is greater than the preset abnormal number of segments 3, and the process goes to step S53; if the number of segments is not greater than (i.e., less than or equal to) the preset number of abnormal segments, the process proceeds to step S6, for example, if the number of segments of the sub video information having the preset abnormal behavior is 3 segments, and the preset number of abnormal segments is 3 segments, the number of segments 3 is not greater than the preset number of abnormal segments 3, and the process proceeds to step S6.
It should be noted that the number of the selected segments of the sub-video is not limited to the above 5 segments, and may also be set according to the actual situation of the user (e.g., local security or indoor property), for example, the local security is poor or the indoor property is valuable, and the number of the selected segments of the sub-video may be set to a smaller value, for example, may be 3 segments or 4 segments; if the local security is good or the property in the room is not valuable, the number of selected segments of the sub-video can be set to a large value, for example, 7 segments or 8 segments.
Similarly, the preset number of abnormal segments is not limited to the above 3 segments, and may also be set according to the actual situation of the user (e.g. local security or indoor property), for example, the local security is poor or the indoor property is valuable, and the preset number of abnormal segments may be set to a smaller value, for example, 2 segments or 1 segment; if the local security is good or the property in the room is not valuable, the number of the default abnormal segments may be set to a large value, for example, 4 or 5 segments.
Specifically, the number of segments of the sub video information in which the preset abnormal behavior exists in the sub video information may be set to the same value as the preset abnormal segment number.
And a substep S53 of determining that an abnormal behavior exists and generating an abnormal behavior warning command.
EXAMPLE III
On the basis of the previous embodiment, the present embodiment provides a monitoring method for monitoring an indoor environment by obtaining image information in each segment of sub-video information, specifically, fig. 4 is another schematic flow chart of the monitoring method according to the embodiment of the present invention, please refer to fig. 4, and step S41 includes:
and a substep S411, acquiring multi-frame image information in each segment of sub-video information.
The number of frames of the image information acquired from each segment of sub-video information can be determined according to the duration of the sub-video information, the duration of the sub-video information can be in direct proportion to the number of frames of the image information, and particularly, when the duration of the sub-video information is longer, the number of frames of the acquired image information is more; when the duration of the sub video information is short, the number of frames of the acquired image information is small. For example, when the duration is 2 minutes, the number of frames of the acquired image information is 5 frames; when the time length is 5 minutes, the number of frames of the acquired image information is 10 frames.
In addition, the manner of acquiring the multi-frame image information from each frame of sub-video information may be random. It is also possible to acquire image information at the same time interval, for example, when the time length is 2 minutes, the number of frames of the acquired image information is 5 frames, and one frame of image information is acquired every 40 seconds.
And a substep S412 of calculating the abnormal probability of each frame of image information in each segment of sub-video information by using a preset convolutional neural network and each frame of image information in each segment of sub-video information.
It should be noted that, the image information with the abnormal behavior is input into a convolutional neural network (CNN for short), and a corresponding relationship between the image information and the abnormal behavior is established, so as to obtain the trained preset convolutional neural network. The more times of training, the higher the accuracy of the obtained preset convolutional neural network.
When the trained preset convolutional neural network is used, inputting each frame of image information into the preset convolutional neural network, extracting the characteristics of each frame of image by the preset convolutional neural network, and obtaining the abnormal probability of each frame of image information as the image with abnormal behaviors according to the extracted characteristics. For example, when a frame of image information is input into a preset convolutional neural network, the obtained abnormal probability is 80%.
And a substep S413 of calculating an average value of the abnormal probabilities of all the image information in each segment of video information to obtain an average abnormal probability of each segment of video information.
For convenience of understanding, the present embodiment shows an example in which, when the image information of each piece of video information is 2 frames, the anomaly probability of one frame of image information is 80%, the anomaly probability of another frame of image information is 90%, and the average anomaly probability of each piece of video information is (80% + 90%)/2 ═ 85%.
And a substep S414 of judging whether each average abnormal probability is greater than a preset abnormal probability.
For example, the average abnormal probability is two, which is 85% and 80%, respectively, when the average abnormal probability is greater than the preset abnormal probability, for example, the preset abnormal probability is 60%, where the average abnormal probability of a segment of sub-video information is 85%, the average abnormal probability is 85% greater than the preset abnormal probability 60%, the process goes to sub-step S511, and it is determined that abnormal behavior exists in the video information with the average abnormal probability of 85%; if the average abnormal probability of the other sub-segment of video is 80%, the average abnormal probability of 80% is greater than the preset abnormal probability of 60%, the process goes to sub-step S511, and it is determined that the video information with the average abnormal probability of 80% has abnormal behavior. If the average abnormal probability is not greater than (i.e., less than or equal to) the predetermined abnormal probability, for example, the predetermined abnormal probability is 90%, wherein 85% of the average abnormal probability of one segment of sub-video information is less than 90% of the predetermined abnormal probability, and 80% of the average abnormal probability of another segment of sub-video information is less than 90% of the predetermined abnormal probability, the process proceeds to step S6.
Step S51 includes:
and a substep S511, determining that abnormal behaviors exist in the sub-video information, and counting the number of the sub-video information sections with preset abnormal behaviors in all the sub-video information.
Continuing with the example in sub-step S414, when the average abnormal probability is two, and is 85% and 80%, respectively, it is determined that there is an abnormality in the sub video information with the average abnormal probability of 85% and 80%, and the number of segments of the sub video information with abnormal behavior is 2 segments.
Example four
On the basis of the foregoing embodiments, the present embodiment provides a monitoring method for controlling an image capturing apparatus to stop working, and specifically, fig. 5 is another schematic flow chart of the monitoring method according to the embodiment of the present invention, and please refer to fig. 5, the monitoring method further includes:
and step S8, acquiring the sound signal collected by the sound collection device.
The sound collection equipment collects indoor sound signals in real time and sends the collected sound signals to the processor. The sound signal may be the dialogue content or the decibel of the sound.
And step S9, when the received sound signal is a second preset sound signal, controlling the camera equipment to stop collecting the video information.
Optionally, when the sound signal is the dialog content, the second preset sound signal may be "end shooting" or "no abnormality", or the like; when the sound signal is a decibel of sound, the second predetermined sound signal may be 30 decibels, 45 decibels, or the like.
In this embodiment, gather the sound signal through sound collection equipment, when the sound signal of gathering is the second and predetermines the sound signal, control camera equipment stop work to guarantee user's privacy, and prevent that the video information under the normal condition from taking up the memory.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
(1) the camera equipment is used for acquiring the video information in real time, so that the occupied memory is large, and the acquisition of the video information is not beneficial to protecting the privacy of the user when the user works and lives normally;
(2) the method comprises the steps that sound collection equipment collects indoor sound signals in real time, when the collected sound signals are first preset sound signals, abnormal behaviors possibly occur indoors, a processor controls camera equipment to work, the camera equipment collects indoor video information, the processor identifies a monitored object in the video information, judges whether the monitored object has the abnormal behaviors or not, if the monitored object has the abnormal behaviors, an abnormal behavior warning instruction is generated, the camera equipment is controlled to track the monitored object to collect the video information, and the life and property safety of a user is guaranteed;
(3) the voice signal is collected through the voice collecting device, when the collected voice signal is the second preset voice signal, the camera shooting device is controlled to stop working, privacy of a user is guaranteed, and the video information under the normal condition is prevented from occupying the memory.
EXAMPLE five
Fig. 6 is a connection block diagram of a monitoring device according to an embodiment of the present invention, and referring to fig. 6, a monitoring device 2 includes: the device comprises an acquisition module 21, a control module 22, an identification module 23, a judgment module 24 and a generation module 25.
The acquiring module 21 is configured to acquire a sound signal acquired by the sound acquiring device.
It is understood that the obtaining module 21 is used for executing the step S1 in the above embodiment.
And the control module 22 is used for controlling the camera equipment to collect the video information when the received sound signal is a first preset sound signal.
It is understood that the control module 22 is configured to execute step S2 in the above-described embodiment.
And the identification module 23 is used for identifying the monitored object in the video information.
It is understood that the identification module 23 is used for executing the step S3 in the above embodiment.
And the judging module 24 is configured to judge whether a preset abnormal behavior exists in the monitored object in the video information.
It is understood that the determining module 24 is used for executing the step S4 in the above embodiment.
And the generating module 25 is configured to generate an abnormal behavior warning instruction when a preset abnormal behavior exists in the monitored object in the video information.
It is understood that the generating module 25 is used for executing the step S5 in the above embodiment.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working processes of the obtaining module 21, the control module 22, the identifying module 23, the judging module 24 and the generating module 25 may refer to corresponding processes in the foregoing method embodiments, and are not described herein again.
EXAMPLE six
The present embodiment provides a storage medium, which stores a computer program, and when the storage medium is executed by one or more processors, the monitoring method according to any one of the first to fourth embodiments is implemented.
The storage medium may be a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc.
EXAMPLE seven
The embodiment provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the monitoring method according to any one of the first to fourth embodiments is executed.
The Processor may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is configured to perform the monitoring method in the first embodiment.
The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk.
In summary, according to the monitoring method, the monitoring device, the home equipment, the storage medium and the electronic equipment provided by the invention, the sound signal collected by the sound collection equipment is obtained, when the received sound signal is the first preset sound signal, the camera equipment is controlled to work, the video information is collected, the monitored object in the video information is identified, whether the monitored object has the preset abnormal behavior or not is judged, and if the monitored object has the preset abnormal behavior, the abnormal behavior warning instruction is generated to warn the monitored object, so that the life and property safety of the user is ensured.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that, in the present invention, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (11)
1. A method of monitoring, the method comprising:
acquiring a sound signal acquired by sound acquisition equipment;
when the received sound signal is a first preset sound signal, controlling the camera equipment to collect video information;
identifying a monitoring object in the video information;
judging whether a monitored object in the video information has a preset abnormal behavior or not;
and if the preset abnormal behavior exists in the monitored object in the video information, generating an abnormal behavior warning instruction.
2. The monitoring method according to claim 1, wherein the video information includes a plurality of segments of sub-video information, and the time length of each segment of sub-video information is the same; the step of judging whether the monitoring object in the video information has a preset abnormal behavior includes:
and judging whether all the sub-video information contains the sub-video information of the monitored object with the preset abnormal behavior.
3. The monitoring method according to claim 2, wherein the step of generating an abnormal behavior warning instruction if the preset abnormal behavior exists in the monitored object in the video information includes:
if the monitored object has the sub-video information with the preset abnormal behavior in all the sub-video information, counting the number of segments of the sub-video information with the preset abnormal behavior in all the sub-video information;
judging whether the number of the sections is larger than a preset abnormal number of the sections;
and if the number of the sections is larger than the preset abnormal number of the sections, determining that the monitored object has abnormal behavior, and generating an abnormal behavior warning instruction.
4. The monitoring method according to claim 3, wherein the step of determining whether there is any sub video information of the preset abnormal behavior of the monitored object in all the sub video information comprises:
acquiring multi-frame image information in each section of the sub-video information;
calculating the abnormal probability of each frame of image information in each section of the sub-video information by utilizing a preset convolutional neural network and each frame of image information in each section of the sub-video information;
calculating the average value of the abnormal probability of all the image information in each section of the video information to obtain the average abnormal probability of each section of the video information;
and judging whether each average abnormal probability is larger than a preset abnormal probability.
5. The monitoring method according to claim 4, wherein the step of counting the number of segments of the sub video information having the preset abnormal behavior in all the sub video information if there is the sub video information having the preset abnormal behavior in the monitored object in all the sub video information comprises:
and if the average abnormal probability is greater than the preset abnormal probability, determining that abnormal behaviors exist in the section of sub-video information, and counting the number of the sections of the sub-video information with the preset abnormal behaviors in all the sub-video information.
6. The monitoring method of claim 1, further comprising:
and if the preset abnormal behavior exists in the video information, controlling the camera equipment to track a monitored object to acquire the video information.
7. The monitoring method of claim 1, further comprising:
acquiring a sound signal acquired by the sound acquisition equipment;
and when the received sound signal is a second preset sound signal, controlling the camera equipment to stop collecting the video information.
8. A monitoring device, comprising:
the acquisition module is used for acquiring the sound signals acquired by the sound acquisition equipment;
the control module is used for controlling the camera equipment to collect video information when the received sound signal is a first preset sound signal;
the identification module is used for identifying a monitored object in the video information;
the judging module is used for judging whether a monitoring object in the video information has a preset abnormal behavior;
and the generating module is used for generating an abnormal behavior warning instruction when the preset abnormal behavior exists in the monitored object in the video information.
9. The household equipment is characterized by comprising sound acquisition equipment, camera equipment and a processor, wherein the sound acquisition equipment and the camera equipment are electrically connected with the processor;
the sound acquisition equipment is used for acquiring sound signals and sending the sound signals to the processor;
the processor is used for controlling the camera equipment to collect video information when the received sound signal is a first preset sound signal;
the processor is further used for receiving the video information acquired by the camera equipment and identifying a monitoring object in the video information;
the processor is further configured to determine whether a preset abnormal behavior exists in a monitored object in the video information; and if the preset abnormal behavior exists in the monitored object in the video information, generating an abnormal behavior warning instruction.
10. A storage medium storing a computer program, the storage medium implementing the monitoring method according to any one of claims 1-7 when executed by one or more processors.
11. An electronic device, comprising a memory and a processor, the memory having stored thereon a computer program which, when executed by the processor, performs the monitoring method of any one of claims 1-7.
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