CN114821949A - Warning method and warning system based on interactive behavior detection - Google Patents
Warning method and warning system based on interactive behavior detection Download PDFInfo
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- CN114821949A CN114821949A CN202110120226.5A CN202110120226A CN114821949A CN 114821949 A CN114821949 A CN 114821949A CN 202110120226 A CN202110120226 A CN 202110120226A CN 114821949 A CN114821949 A CN 114821949A
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- 230000002452 interceptive effect Effects 0.000 title claims abstract description 21
- 238000001514 detection method Methods 0.000 title claims abstract description 17
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000012502 risk assessment Methods 0.000 claims abstract description 71
- 230000003993 interaction Effects 0.000 claims abstract description 39
- 241001465754 Metazoa Species 0.000 claims description 10
- 230000006399 behavior Effects 0.000 description 30
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- 206010000117 Abnormal behaviour Diseases 0.000 description 1
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B19/00—Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
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Abstract
An alarming method and system based on interactive behavior detection. The method comprises the following steps: detecting the type of a first target object in a target area through an image recognition module; detecting the type of a second target object in the target area through the image recognition module; determining a risk assessment model according to the type of the first target object and the type of the second target object; detecting an interaction behavior between the first target object and the second target object through the image recognition module; and sending out warning information according to the risk assessment model and the interaction behavior so as to warn the first target object by the warning information.
Description
Technical Field
The present invention relates to a risk assessment and warning technology, and more particularly, to a warning method and warning system based on interactive behavior detection.
Background
In daily life, many dangerous or unexpected occurrences are closely related to the behavior of people in mind. However, the conventional security systems mainly perform post-treatment such as alarm issuing and fire extinguishing for accidents (e.g. fire) that have occurred, and cannot detect and try to prevent the accidents before the accidents occur.
Disclosure of Invention
The invention provides a warning method and a warning system based on interactive behavior detection, which can try to detect and prevent possible accidents according to interactive behaviors among different types of objects.
The embodiment of the invention provides an alarm method based on interactive behavior detection, which comprises the following steps: detecting the type of a first target object in a target area through an image recognition module; detecting the type of a second target object in the target area through the image recognition module; determining a risk assessment model according to the type of the first target object and the type of the second target object; detecting an interaction behavior between the first target object and the second target object through the image recognition module; and sending out warning information according to the risk assessment model and the interaction behavior so as to warn the first target object by the warning information.
The embodiment of the invention also provides an alarm system based on interactive behavior detection, which comprises an image acquisition interface, an image identification module, an alarm device and a processor. The image capturing interface is used for capturing a target image corresponding to the target area. The image identification module is used for executing image identification operation on the target image. The processor is coupled to the image capturing interface, the image identification module and the warning device. The processor is configured to: detecting the type of a first target object in the target area through the image recognition module; detecting the type of a second target object in the target area through the image recognition module; determining a risk assessment model according to the type of the first target object and the type of the second target object; detecting an interaction behavior between the first target object and the second target object through the image recognition module; and indicating the warning device to send warning information according to the risk assessment model and the interaction behavior so as to warn the first target object by the warning information.
Based on the above, the image recognition module can detect the types of a plurality of target objects in the target area and determine a risk assessment model according to the types. According to the interaction behavior between the risk assessment model and the targets, a warning message can be sent out to warn the targets through the warning message. Thereby, attempts can be made to detect and prevent possible risk events.
Drawings
Fig. 1 is a functional block diagram of an alert system based on interactive behavior detection according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a target image according to an embodiment of the invention.
Fig. 3 is a flowchart illustrating an alert method based on interactive behavior detection according to an embodiment of the present invention.
Wherein:
100, an alarm system based on interactive behavior detection;
10, a host device;
11, image capturing interface;
12, a storage device;
13, a warning device;
14, a processor;
21, target image;
201,202, a target object;
s301 to S305.
Detailed Description
Fig. 1 is a functional block diagram of an alert system based on interactive behavior detection according to an embodiment of the present invention. Referring to fig. 1, a system (also referred to as an alert system based on interactive behavior detection) 100 includes an image capturing interface 11, a storage device 12, an alert device 13, and a processor 14.
The image capturing interface 11 is used for capturing an external image (also referred to as a target image). The target image may include an image of an area (also referred to as a target area). For example, the image capturing interface 11 may include a combination of a lens and an image capturing device such as a photosensitive module. In addition, the number of the image capturing interfaces 11 may be one or more, so as to capture the target images individually or together.
The storage device 12 is used to store data (such as image data of the target image). For example, the storage circuit 12 may include a volatile memory module and a non-volatile memory module. The volatile memory module can be used for storing data in a volatile mode. The non-volatile memory module can be used for non-volatile data storage. For example, the volatile Memory module may include a Dynamic Random Access Memory (DRAM), and the non-volatile Memory module may include a Hard Disk Drive (HDD) and/or a Solid State Drive (SSD).
The warning device 13 is used for sending warning information. For example, the warning device 13 may send out warning information related to vision or hearing to the target area. For example, in one embodiment, the warning device 13 may include one or more displays. The display can display the warning information in the form of an image. Alternatively, in one embodiment, the warning device 13 may include one or more speakers. The speaker may emit the warning message in the form of a sound, such as a warning tone.
The processor 14 is coupled to the image capturing interface 11, the storage device 12 and the warning device 13. Processor 14 may be responsible for the overall or partial operation of system 100. For example, the Processor 14 may include any Programmable general purpose or special purpose microprocessor, Digital Signal Processor (DSP), Programmable controller, Application Specific Integrated Circuit (ASIC), Programmable Logic Device (PLD), or the like, or any combination thereof.
In one embodiment, each of the components of the system 100 (e.g., the image capture interface 11, the storage device 12, the alert device 13, and the processor 14) may be implemented in a single host device 10. For example, the host device 10 may resemble a monitor in appearance and may be disposed near the target area. In one embodiment, the various components of the system 100 may be distributed among multiple devices. For example, the image capturing interface 11 may be implemented as a monitor, the warning device 13 may be implemented as a speaker, and the storage device 12 and the processor 14 may be disposed in a host device. The image capturing interface 11 and the warning device 13 may be disposed near the target area, and the storage device 12 and the processor 14 may be disposed at any location (e.g., near the target area or in a remote server). In one embodiment, the system 100 may further include other types of input/output media, such as a microphone (for receiving sound signals in the target area), a display (for displaying the target image), a mouse, a keyboard, or a network connection medium, etc., which are not limited by the invention.
In one embodiment, the storage device 12 stores an image recognition module 101. The image recognition module 101 may perform an automated image recognition operation on the target image based on an image recognition technique. In one embodiment, the image recognition module 101 may also be implemented as a hardware circuit (e.g., an image processing chip).
In one embodiment, the processor 14 may detect the type of the object (also referred to as the first object) in the target area by the image recognition module 101. Meanwhile, the processor 14 may detect the type of another object (also referred to as a second object) in the target area through the image recognition module 101.
In one embodiment, the type of object may be a human, an animal other than a human, or an object. In one embodiment, the type of object may be further subdivided into a specific type of human, a specific type of animal, or a specific type of object. For example, the particular type of person may be distinguished by occupation, age, and/or gender. Taking an animal as an example, the particular type of animal may be a cat, dog, or other animal. Alternatively, the specific type of object may be distinguished by the type, purpose and/or function of the object, for example. The processor 14 may identify the type of one or more objects in the target image by the image recognition module 101.
In one embodiment, processor 14 may determine a risk assessment model based on the type of the first object and the type of the second object. It is noted that combinations of particular types of targets may correspond to particular risk assessment models. Combinations of different types of targets may correspond to different risk assessment models.
In one embodiment, the processor 14 may detect an interaction between the first object and the second object through the image recognition module 101. Then, the processor 14 may send out warning information according to the determined risk assessment model and the interactive behavior indication warning device 13, so as to warn the target object in the target area by the warning information.
In one embodiment, the processor 14 may determine whether the detected interaction between the first object and the second object meets an alert trigger condition defined by the determined risk assessment model. If the interaction behavior meets the alarm triggering condition defined by the determined risk assessment model, the processor 14 may instruct the alarm device 13 to send out the alarm information, so as to alarm the target object in the target area with the alarm information. Furthermore, if the interaction behavior does not meet the alert triggering condition defined by the determined risk assessment model, the processor 14 may not instruct the alert device 13 to issue the alert message.
In one embodiment, processor 14 may determine the risk assessment model based on a combination of the type of the first object and the type of the second object. For example, in one embodiment, processor 14 may determine the risk assessment model as a risk assessment model (also referred to as a first risk assessment model) assuming that the type of the first object and the type of the second object conform to a certain type combination (also referred to as a first type combination). The first risk assessment model may define an alert trigger condition (also referred to as a first alert trigger condition). In a state of using the first risk assessment model, if the detected interaction behavior between the first target object and the second target object meets the first alarm triggering condition defined by the first risk assessment model, the processor 14 may instruct the alarm device 13 to send out the alarm information.
Alternatively, in one embodiment, processor 14 may determine the risk assessment model as another risk assessment model (also referred to as a second risk assessment model) assuming that the type of the first object and the type of the second object conform to another type combination (also referred to as a second type combination). The second risk assessment model may define another alert trigger condition (also referred to as a second alert trigger condition). In a state of using the second risk assessment model, if the detected interaction behavior between the first target object and the second target object meets a second alarm triggering condition defined by the second risk assessment model, the processor 14 may send out the alarm information. Wherein the second type combination is different from the first type combination, the second risk assessment model is different from the first risk assessment model, and the second alert trigger condition is different from the first alert trigger condition. In addition, the information content of the alarm information sent out according to different interaction behaviors and/or different alarm triggering conditions may also be different.
In the following embodiments, it is assumed that the warning information is used to warn the first target object in the target area. Thus, the type of the first object may be a human or an animal other than a human, and the type of the second object may be a human, an animal other than a human, or an object. The processor 14 may detect a relative position between the first object and the second object and/or detect a posture of the first object by the image recognition module 101. The processor 14 may then determine the interaction behavior between the first object and the second object according to the relative position and/or posture of the first object.
Fig. 2 is a schematic diagram of a target image according to an embodiment of the invention. Referring to fig. 2, the objects 201 and 202 in the object image 21 and their types can be detected. For example, the type of the object 201 may be detected as a person or a cook, and the type of the object 202 may be detected as a dangerous object, an object requiring a long time to pay attention, or a fire. Depending on the type combination of objects 201 (e.g. chefs) and 202 (e.g. stoves), a corresponding risk assessment model may be decided upon. Then, the interaction between the objects 201 and 202 can be continuously detected according to the position of the object 201, the limb movement track, the face orientation, the limb movement, the relative position between the objects 201 and 202, the position of the object 202, and/or the state of the object 202 (e.g., turned on or off).
At some point in time, an alert message may be issued if the measured interaction between the targets 201 and 202 meets the alert trigger defined by the determined risk assessment model (e.g., the target 201 does not return to the front of the target 202 or focus on the target 202 after a predetermined period of time while the target 202 is in a fired state). For example, the warning message may be sent through a speaker to warn or remind the object 201 to check the status of the object 202. Therefore, the probability of fire caused by the situation that the cook does not pay attention to the operation state of the stove for a long time can be reduced.
It should be noted that the type combinations of the objects 201 and 202 in fig. 2 may be changed in different usage scenarios. Meanwhile, a risk assessment model for detecting whether the interaction between the objects 201 and 202 triggers an alarm may be determined and used accordingly.
In one embodiment, assume that object 201 in FIG. 2 is of the type caregiver (e.g., babysitter) and object 202 is of the type that is being attended (e.g., child). After identifying the types of objects 201 and 202, a risk assessment model corresponding to the type combination of objects 201 and 202 may be determined. Meanwhile, the interaction behavior between the objects 201 and 202 (e.g., the position of the object 201, the limb movement trajectory, the face orientation, the limb movement, the relative position between the objects 201 and 202, the position of the object 202, and/or the state of the object 202) can be continuously detected.
At some point in time, an alert message may be issued if the measured interaction between the targets 201 and 202 meets the alert trigger condition defined by the determined risk assessment model (e.g., the target 201 does not return to the front of the target 202 or focuses on the target 202 after a predetermined period of time). For example, the warning message may be sent through a speaker to warn or remind the object 201 to check the status of the object 202. Therefore, the probability of accidents of the caretaker caused by the fact that the caretaker does not pay attention to the caretaker for a long time can be reduced.
In one embodiment, assume that the type of object 201 in FIG. 2 is a patrol officer (e.g., security guard) and the type of object 202 is a particular location. After identifying the types of objects 201 and 202, a risk assessment model corresponding to the type combination of objects 201 and 202 may be determined. Meanwhile, the interaction behavior between the objects 201 and 202 (e.g., the position of the object 201, the limb movement trajectory, the face orientation, the limb movement, the relative position between the objects 201 and 202, the position of the object 202, and/or the state of the object 202) can be continuously detected.
At some point in time, an alert message may be issued if the measured interaction between the objects 201 and 202 meets the alert trigger condition defined by the determined risk assessment model (e.g., the object 201 has not passed in front of the object 202 or is interested in the object 202 after a predetermined period of time). For example, the warning message may be sent through a speaker to warn or remind the object 201 to check the status of the object 202. Therefore, the probability that the patrol personnel is invaded by other people in the specific place due to the fact that the patrol personnel does not go to the specific place for patrol for a long time can be reduced.
In one embodiment, assume that the type of object 201 in FIG. 2 is an unknown person (e.g., stranger) and the type of object 202 is a specific object or a specific location. After identifying the types of objects 201 and 202, a risk assessment model corresponding to the type combination of objects 201 and 202 may be determined. Meanwhile, the interaction behavior between the objects 201 and 202 (e.g., the position of the object 201, the limb movement trajectory, the face orientation, the limb movement, the relative position between the objects 201 and 202, the position of the object 202, and/or the state of the object 202) can be continuously detected.
At a certain time point, if the measured interaction between the objects 201 and 202 meets the alarm triggering condition defined by the determined risk assessment model (for example, the staying time or the occurrence frequency of the object 201 in front of the object 202 exceeds a preset value), an alarm message may be issued. For example, the warning message may be sent through a speaker to warn or remind the target 201 that the abnormal behavior has been detected. Therefore, the probability that a specific object is stolen or a specific place is invaded under the unattended condition can be reduced.
It should be noted that although examples of the use of various combinations of types of objects and corresponding risk assessment models have been proposed in the foregoing embodiments, in reality, the combinations of types of objects may have more variations than those described above. Meanwhile, the risk assessment model can be selected or set according to different types of target objects, so that corresponding warning information is generated. The details of the operation are described above, and are not repeated herein.
Fig. 3 is a flowchart illustrating an alert method based on interactive behavior detection according to an embodiment of the present invention. Referring to fig. 3, in step S301, the type of the first target object in the target area is detected by the image recognition module. In step S302, the type of a second target object in the target area is detected through the image recognition module. In step S303, a risk assessment model is determined according to the type of the first object and the type of the second object. In step S304, an interaction between the first object and the second object is detected by the image recognition module. In step S305, an alert message is issued according to the risk assessment model and the interaction behavior, so as to alert the first target object by the alert message.
However, the steps in fig. 3 have been described in detail above, and are not described again here. It is to be noted that, the steps in fig. 3 can be implemented as a plurality of program codes or circuits, and the invention is not limited thereto. In addition, the method of fig. 3 can be used with the above embodiments, and can also be used alone, and the invention is not limited thereto.
In summary, the image recognition module can detect the types of the target objects in the target area and determine a risk assessment model according to the types. According to the interaction behavior between the risk assessment model and the targets, a warning message can be sent out to warn the targets through the warning message. Thus, prior to occurrence of a risk event, attempts may be made to detect and prevent the risk event from occurring. In addition, since the type of the target object in the target area can be automatically detected and the corresponding risk assessment model can be automatically selected, the method and the system provided by the embodiment of the invention also have high convenience in use, thereby improving the user experience.
Although the present invention has been described with reference to the above embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention.
Claims (10)
1. An alert method based on interactive behavior detection includes:
detecting the type of a first target object in a target area through an image identification module;
detecting the type of a second target object in the target area through the image recognition module;
determining a risk assessment model according to the type of the first target object and the type of the second target object;
detecting an interaction behavior between the first target object and the second target object through the image recognition module; and
and sending out warning information according to the risk assessment model and the interaction behavior so as to warn the first target object by the warning information.
2. The method of claim 1, wherein the step of determining the risk assessment model according to the type of the first object and the type of the second object comprises:
determining the risk assessment model as a first risk assessment model if the type of the first object and the type of the second object conform to a first type combination; and
determining the risk assessment model as a second risk assessment model if the type of the first object and the type of the second object match a second type combination,
wherein a first alert trigger condition defined by the first risk assessment model is different from a second alert trigger condition defined by the second risk assessment model.
3. The method as claimed in claim 1, wherein the first object is a human or an animal, and the second object is a human, an animal or an object.
4. The method as claimed in claim 1, wherein the step of detecting the interaction between the first object and the second object via the image recognition module comprises:
detecting the relative position between the first target object and the second target object;
detecting the posture of the first target object; and
and determining the interaction behavior between the first target object and the second target object according to the relative position between the first target object and the second target object and the posture of the first target object.
5. The method as claimed in claim 1, wherein the step of sending the warning message according to the risk assessment model and the interactive behavior comprises:
judging whether the interaction behavior meets a warning triggering condition defined by the risk assessment model; and
and if the interaction behavior conforms to the warning triggering condition defined by the risk assessment model, sending out the warning information.
6. An alert system based on interactive behavior detection, comprising:
an image capturing interface for capturing a target image corresponding to a target area;
an image identification module for performing an image identification operation on the target image;
a warning device;
a processor coupled to the image capture interface, the image recognition module and the warning device, wherein the processor is configured to:
detecting the type of a first target object in the target area through the image recognition module;
detecting the type of a second target object in the target area through the image recognition module;
determining a risk assessment model according to the type of the first target object and the type of the second target object;
detecting an interaction behavior between the first target object and the second target object through the image recognition module; and
and indicating the warning device to send out warning information according to the risk assessment model and the interaction behavior so as to warn the first target object by the warning information.
7. The interactive behavior detection-based alert system of claim 6, wherein the operation of determining the risk assessment model based on the type of the first object and the type of the second object comprises:
determining the risk assessment model as a first risk assessment model if the type of the first object and the type of the second object conform to a first type combination; and
determining the risk assessment model as a second risk assessment model if the type of the first object and the type of the second object match a second type combination,
wherein a first alert trigger condition defined by the first risk assessment model is different from a second alert trigger condition defined by the second risk assessment model.
8. The interactive behavior detection-based warning system of claim 6, wherein the first object is a person or an object and the second object is a person, an animal or an object.
9. The warning system as claimed in claim 6, wherein the operation of detecting the interaction between the first object and the second object via the image recognition module comprises:
detecting the relative position between the first target object and the second target object;
detecting the posture of the first target object; and
and determining the interaction behavior between the first target object and the second target object according to the relative position between the first target object and the second target object and the posture of the first target object.
10. The system of claim 6, wherein the operation of instructing the alert device to send the alert message according to the risk assessment model and the interactive behavior comprises:
judging whether the interaction behavior meets a warning triggering condition defined by the risk assessment model; and
and if the interaction behavior conforms to the warning triggering condition defined by the risk assessment model, indicating the warning device to send out the warning information.
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| CA2295378A1 (en) * | 1998-12-31 | 2000-06-30 | Steve Mann | Point of purchase (pop) terminal |
| CN1747550A (en) * | 2004-09-10 | 2006-03-15 | 樊珅溪 | Image tracing and monitoring alarm system |
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