WO2013107145A1

WO2013107145A1 - Video identification technology-based system and method for providing value-added service

Info

Publication number: WO2013107145A1
Application number: PCT/CN2012/076669
Authority: WO
Inventors: 邢晓江
Original assignee: 中兴通讯股份有限公司
Priority date: 2012-01-17
Filing date: 2012-06-08
Publication date: 2013-07-25
Also published as: CN102543124B; CN102543124A

Abstract

Disclosed is a video identification technology-based system for providing a value-added service, comprising: a preprocessing module and an application module, where the preprocessing module is configured to identify video data and to store the identification result by means of a formatted markup text, and where the application module is configured to provide the value-added service on the basis of the identification result stored by the preprocessing module. Correspondingly, also disclosed is a video identification technology-based method for providing the value-added service. The present invention allows for reduced storage space of the video data in a video surveillance system and for facilitated monitoring, indexing, and sharing of the video data.

Description

System and method for providing value-added service based on video recognition technology

The present invention relates to video processing technologies, and more particularly to a system and method for providing value-added services based on video recognition technology. Background technique

Video surveillance is a common application in the Internet of Things system. It plays a very important role in people's lives and work. For example, the city security video surveillance system as a safe city construction, public security "scientific and technical police" and public security information An important part of the construction has been highly valued by the State Council, the Ministry of Public Security, local governments at all levels, and public security organs. In just a few years, the world’s largest and most widely covered video surveillance system has been built. It has made a good contribution to improving the security situation of the city, strengthening urban management, and creating a harmonious society.

As of the end of 2010, approximately 20 million cameras were deployed nationwide, of which more than 3 million were deployed by the public security department. There are also some problems with such a huge video surveillance system, mainly in:

1) Huge storage pressure. The resolution of the camera is about 1.2 million to 2 million pixels. Each camera generates about 100M of video data per hour. Ten thousand cameras produce 24TB of data every day. Although there are some intelligent compression technologies, the storage pressure is extremely high. .

2) A large number of people are required to watch manually, and the retrieval is difficult. These videos are currently monitored mainly by manual viewing. In a city in southern China, 500,000 cameras have been deployed, of which 230,000 are deployed by the public security department, and 1,800 people have to be hired to watch these cameras. The search is difficult, almost entirely through manual viewing.

3) Cross-domain sharing and joint coordination are difficult. Based on existing video surveillance methods, information sharing and joint coordination between systems and systems, between departments and departments, between cities and cities is difficult. 4) It is difficult to link with other systems. Based on the existing video surveillance system, it is difficult to achieve linkage with other systems in the city. Because of the difficulty in information sharing, the video surveillance system has become an "information island." Summary of the invention

In view of this, the main purpose of the embodiments of the present invention is to provide a system and method for providing value-added services based on video recognition technology, which can reduce the storage space of video data in applications such as video surveillance, and facilitate video data monitoring, retrieval, and sharing.

To achieve the above objective, the technical solution of the embodiment of the present invention is implemented as follows:

A system for providing value-added services based on video recognition technology, comprising: a pre-processing module and an application module; wherein

The pre-processing module is configured to identify the video data, and store the recognition result in a formatted text manner;

The application module is configured to provide a value-added service based on the identification result stored by the pre-processing module. The system also includes an optimization module.

The optimization module is configured to optimize the recognition result of the pre-processing module.

The system also includes a manual intervention module.

The manual intervention module is configured to implement interaction with the user, control the recognition process according to user operations, or modify the recognition result.

The system also includes a video capture module.

The video capture module is configured to collect video data for identification by the pre-processing module; the optimization module is further configured to optimize the video capture module;

The manual intervention module is further configured to control the video collection module according to a user operation. A method for providing value-added services based on video recognition technology, including:

Identify video data;

The recognition result is stored in a text formatted by the format ^;

A value added service is provided based on the recognition result. The method also includes: optimizing the identification of the video data.

The method further includes: controlling the recognition process according to a user operation or modifying the recognition result.

The method further includes: optimizing parameters related to video capture, and/or controlling the video capture process according to user operations.

Embodiments of the present invention provide a system and method for providing value-added services based on video recognition technology, identify video by video recognition technology, mark various types of information identified by a formatting language, and then perform a database or other structured manner. Stored, structured tagged information that provides a variety of value-added services (such as video surveillance). The technical solution described in the embodiments of the present invention can reduce the storage space of video data in the video surveillance system, and is beneficial to monitoring, retrieving, and sharing video data. BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a schematic diagram of a system structure for providing value-added services based on video recognition technology according to an embodiment of the present invention;

2 is a schematic structural diagram of another system for providing value-added services based on video recognition technology according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of another system for providing value-added services based on video recognition technology according to an embodiment of the present invention; FIG.

4 is a schematic diagram of a system structure for providing value-added services based on video recognition technology according to an embodiment of the present invention;

FIG. 5 is a schematic flowchart of a method for providing a value-added service based on a video recognition technology according to an embodiment of the present invention. The basic idea of the embodiment of the present invention is: Identifying a video by using a video recognition technology, The various identified information is tagged by the formatting language, and the optimization can be optimized through optimization and manual intervention modules, and then various value-added services are provided based on structured or tagged information stored in a database or other structured manner. .

It should be noted that the video recognition technology analyzes, extracts and features the individual video from the video by designing a certain computer algorithm to determine whether it meets certain rules, whether it belongs to some situations that need to be processed, and reminds.

At present, the data captured by the camera mainly includes: information on people, vehicles, traffic, traffic flow, crowd convergence, etc., which can be technically identified.

The main types of services currently available include:

Video recognition service: Identify specific objects, such as faces, license plates, and photos for comparison;

Video Analysis Services: Provide services such as perimeter intrusion detection, object motion monitoring, traffic flow, traffic statistics, PTZ (Pan/Tilt/Zoom) automatic tracking, etc.

Video Improvement Service: Provides night vision image enhancement processing, image stabilization system and other functions. FIG. 1 is a schematic structural diagram of a system for providing a value-added service based on a video identification technology according to an embodiment of the present invention. As shown in FIG. 1, the system includes: a pre-processing module and an application module;

a pre-processing module configured to identify the video data and store the recognition result in a text format of the formatted mark;

The application module is configured to provide a value-added service based on the recognition result stored by the pre-processing module. The markup language describes various content information recognized by the preprocessing module. For example, the pre-processing module can identify the car, person, and status information in the video content, identify the vehicle color, the model, the license plate, and the like, and identify the information of the bicycle, the electric vehicle, and the motorcycle for the vehicle; Information such as height, men and women, clothing, etc. are identified; in addition, status information such as crowd gathering, congestion, and car accidents can be identified. Here, the pre-processing module can store the identified information in a database manner. To provide to the application module.

For example, the services and applications provided by the application module based on the identified information can be:

1) rapid retrieval service;

2) Save storage space services. For example, if the video segment without information is checked, the video segment may be deleted, or the information in the video may be identified, and the related image storage may be selected;

3) Information services. The information service described here provides the identified information in various ways, for example, it can be pushed, triggered, linked, and the like.

Optionally, as shown in FIG. 2, the system further includes an optimization module.

The optimization module is configured to optimize the recognition result of the pre-processing module to improve the recognition accuracy. For example, in order to improve the image recognition accuracy, the image may be optimized according to the background, brightness, and weather conditions of the camera.

Optionally, as shown in FIG. 3, the system further includes a manual intervention module.

The manual intervention module is configured to implement interaction with the user, control the recognition process according to the user operation, or modify the recognition result to achieve the purpose of automatic re-optimization of the system, and improve the recognition accuracy rate. For example, when an operator finds that an object is not accurately identified, the effect of the recognition can be corrected.

Optionally, as shown in FIG. 4, the system further includes a video capture module.

The manual intervention module is further configured to control the video collection module according to a user operation. The main interfaces of the above systems include:

1) An interface between the pre-processing module and the video acquisition module to enable reading of video data.

2) Optimizing the interface between the module and the pre-processing module. The optimization module provides information such as the background, brightness, and weather conditions of the camera to be optimized to the pre-processing module through the interface; in addition, when the image data does not meet the pre-processing requirements When the preprocessing module can pass the interface to the optimization module For optimization, the results of the pre-processing can also be provided to the optimization module through this interface to support optimization.

3) The interface between the manual intervention module and the pre-processing module realizes the manual intervention of the recognition result or the process. For example, when the operator sees that the recognition result is incorrect, the identification result is forcibly modified through the interface, so that the pre-processing module is improved. Identifying the success rate, and allowing the pre-processing module to re-optimize according to the corrected result; in addition, when the image data does not meet the requirements of the pre-processing, the pre-processing module can provide manual intervention to the manual intervention module through the interface, pre-processing The results can also be provided to the manual intervention module through the interface to support manual intervention;

4) The interface between the pre-processing module and the application module, that is, the stored interface of the identified structured data to the application, which may be an open interface of the database and supports SQL.

5) optimizing the interface between the module and/or the manual intervention module and the video acquisition module, so that the optimization module and/or the manual intervention module can adjust the resolution of the camera, or the parameters of the pan/tilt, camera direction, and angle of view through the interface, Video data is easier to identify.

The embodiment of the present invention further provides a method for providing a value-added service based on the video identification technology. As shown in FIG. 5, the method includes:

Step 501: Identify video data.

Here, the identification of the video data may be further optimized, and/or the recognition process may be controlled according to the user operation or the recognition result may be modified to improve the recognition accuracy.

It should be noted that the video data may be real-time or offline video data, and the specific video format is not limited. When the video content is recognized, the car, the person, and the status information may be identified according to preset requirements. Information such as vehicle color, vehicle type, and license plate is recognized for the vehicle; information on bicycles, electric vehicles, and motorcycles is recognized; people recognize information such as height, men, women, and clothing; and the situation information identifies information such as crowd gathering, congestion, and car accidents.

Step 502: Store the recognition result in the formatted text.

For example, a format language can describe vehicle information as:

Time, camera, video location, location, vehicle model, license plate, vehicle color, speed, In the lane, whether there is any violation of regulations...

The formatted language can describe the person information as:

Time, camera, video location, location, men and women, height, clothes situation, pants situation, hat condition, speed, hand held items...

The formatting information can be described as a formatted language:

Time, camera, video location, location, crowd gathering, vehicle congestion, car accident... It should be noted that the database can be selected to store the formatted tag information.

Step 503: Provide a value-added service based on the identification result.

For example, step 503 may specifically be:

The user inputs the query condition, and the condition may include all the units in the retrieved information of the above structured description;

Search in the database;

According to the retrieved results, combined with the camera information and video location information, find the relevant video, and directly locate the location, you can directly watch it.

For example, step 503 may specifically be:

Extract photos containing various people, cars, and information based on the stored information;

Store the photo and create a query method, you can add a column to the database to store the location where the image is stored;

Delete the original big data video.

For another example, step 503 may specifically be:

Develop an information triggering strategy, including three parts, the conditions of the trigger, the organization and delivery of the information, and the destination of the information;

Load this strategy in the preprocessing module;

When the pre-processed result of the pre-processing module satisfies the trigger condition, the corresponding information is provided to the destination of the information according to the information organization and provision method defined in the policy. The information triggering policy may be: when the crowd is detected, the description text and the picture are sent to the security personnel's mobile phone in a multimedia message manner.

It should be noted that the present invention can also optimize parameters related to video acquisition, and/or control the video collection process according to user operations. Marking, and then providing various value-added services based on structured markup information stored in a database or other structured manner, can reduce the storage space of video data in applications such as video surveillance, and facilitate video data monitoring and retrieval. shared.

The above is only the preferred embodiment of the present invention and is not intended to limit the scope of the present invention.

Claims

Claim

A system for providing value-added services based on video recognition technology, wherein the system comprises: a pre-processing module and an application module; wherein

The application module is configured to provide a value-added service based on the identification result stored by the pre-processing module.

2. The system according to claim 1, wherein the system further comprises an optimization module, the optimization module being configured to optimize the recognition result of the pre-processing module.

3. The system of claim 1 or 2, wherein the system further comprises a manual intervention module,

The system of claim 3, wherein the system further comprises a video capture module, the video capture module is configured to collect video data for recognition by the pre-processing module; and the optimization module is further configured as a video capture module. optimize;

The manual intervention module is further configured to control the video collection module according to a user operation.

5. A method for providing value-added services based on video recognition technology, wherein the method comprises: identifying video data;

The recognition result is stored in a text formatted by the format ^;

A value added service is provided based on the recognition result.

6. The method according to claim 5, wherein

The method also includes: optimizing the identification of the video data.

7. The method according to claim 5 or 6, wherein

8. The method according to claim 7, wherein the method further comprises: optimizing parameters related to video capture, and/or controlling the video capture process according to user operations.