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First, the traditional way of video retrieval <br> <br> in the practical application security video surveillance system, users often want from a flood of tens of thousands of video cameras, making it easy to find some obvious features quickly People or things. The traditional video retrieval methods based on preset alarms and time are often ineffective for such deep-seated needs. They often have the regret of “scratchingâ€. Therefore, how to quickly and accurately perform intelligent retrieval becomes an important issue that large-scale video surveillance systems need to solve. .
The traditional video retrieval method is mainly "human sea tactics" and the efficiency is very low. The main reasons are as follows: First, due to human physiology limitations, focusing on a single video screen for a long time, it is easy to cause the criminal investigators to have low attention and visual fatigue, which seriously affects the efficiency of review; second, the human eye cannot overcome the error. Because of the visual fatigue of the human eye, it is easy to ignore important target clues and create a situation in which people are too blind to the brain. People cannot concentrate on monotonous things for a long time. Therefore, a video often takes more time. Repeated examinations have greatly increased the workload, and still can not completely avoid omissions and errors; Third, it takes too much time to obtain effective information, usually a case needs to look around dozens of cameras, several days before and after the video, The amount of video viewed often reaches hundreds of thousands of hours. Under the current mode of review, traditional methods need to be played from beginning to end, often requiring several times the time of the original video to complete the review. Therefore, a large number of people need to work overtime for several weeks to review the video. In order to avoid omissions and errors, many criminal investigation teams use methods that increase human input. However, it has been proved by practice that this method is not very satisfying, and when such key information is found, criminals are likely to have done more damage.
Second, the status of intelligent video retrieval technology <br> <br> retrieve video surveillance of persons of concern to the video data, the main purpose is to locate and find the cause of an event associated with the development process, key information data events include: Time , location, person or thing, image and sound information of the dominant event. The more information the retrieval conditions convey, the more accurate the positioning, and the simpler the retrieval algorithm. On the contrary, the simpler the information transmitted by the retrieval conditions, the more vague the positioning and the more difficult the retrieval algorithm is when it is desired to accurately position. In general, the user expects the search conditions to be simple and accurate at the same time.
The advent of intelligent video retrieval technology has liberated people from monotonous and heavy tasks. It uses technologies such as video segmentation, automatic digitization, speech recognition, shot detection, key frame extraction, automatic content association, and video structuring. It is based on knowledge in the fields of image processing, pattern recognition, computer vision, and image understanding, and is automated. The intelligent analysis preprocessing will sort out the chaotic and non-logical monitoring video content (moving objects, pedestrians, and vehicles), automatically acquire the key information of the in-video events and targets, and generate video content and indexes based on these information. In order to increase the speed of calculation, clustering methods are currently used, which can provide tens of times more rapid analysis capabilities than real-time, and can be expanded according to application needs, improve computing capacity, and save time in handling cases.
Fundamentally, video retrieval technology applied to security monitoring is based on intelligent video analysis technology. Intelligent video analysis technology refers to the use of computer vision visual analysis technology to analyze and track the targets that appear in the camera scene by separating the background and the target in the scene. In recent years, the term “big data†has been increasingly mentioned and used, involving various industries. People use it to describe and define the massive data generated during the information explosion era. The introduction of intelligent video analysis technology may greatly improve the retrieval efficiency and hit rate of the original massive surveillance video storage system.
In the intelligent video retrieval process, the user can obtain the desired key information from the massive video through the intelligent video analysis technology according to his desired search conditions. The current intelligent video retrieval methods mainly include the following categories:
1. Movement target attribute analysis The target movement attribute includes the target's movement trajectory, movement amplitude, speed and law and other factors. The retrieval based on the target trajectory means that by selecting a specific area in the video, the target entering or leaving the area, and staying in the area, the video retrieval algorithm can quickly focus on the objects that have appeared in the area at all times.
You can also filter the type of the target legend or the results of the investigation. When there are many target results, the system supports the separation of the types in the target and further narrows the scope of interest, such as people and colors.
2. Face Indexing Content-based image retrieval is a hot research topic in recent years, involving subjects such as image processing, computer vision, and database systems. Among them, an effective high-dimensional indexing mechanism is a key technology that enables retrieval of large-scale image libraries to meet real-time requirements.
The current technology mainly collects and summarizes the faces in the surveillance video through intelligent analysis preprocessing and face detection algorithms, obtains relevant information of the target of interest within the video, and generates an index based on these face information. By looking at the face icon, the relevant person can view all the objects contained in the video for several hours in a few minutes, determine the suspect target, and watch the existence segment and the motion track of the target in the entire video.
In the system, the face photo to be queried is input, the face to be searched is selected, the similarity and other parameters are set, and the search is started. The result of the similar face retrieved last time is displayed on the interface.
3, vehicle information identification Through intelligent intelligent analysis pre-processing and intelligent investigation under the rules, the content of the surveillance video is collected and summarized, and the relevant information of the target of interest in the video is obtained, and an index is generated based on the information, mainly based on the license plate. Information presentation. By looking at the license plate legend, the relevant person can find the target license plate within a few minutes and watch the existence of the target in the entire video.
The user can select the video to be played, this video contains the real useful vehicle information (the license plate) that the user is concerned about. The user can perform slow playback according to the content of attention, and the content of no attention is played in a fast-forward manner.
Third, look to the future <br> <br> intelligent video video retrieval technology has been rapid development, improve the accuracy and efficiency of application of intelligent video retrieval products, at the same time improve the core algorithm, at this stage would continue to the following aspects Efforts: First of all, with smart video surveillance technology, cloud computing, Internet of Things and other next-generation technologies combined to expand the scope of more intelligent video applications. Secondly, based on the needs of industry users, we must introduce differentiated market services and develop more targeted products to meet the needs of the on-site environment and improve the discriminative capabilities of products. Third, we must strengthen our R&D efforts and continue to improve our product performance indicators.
With the advent of big data era, intelligent video retrieval technology will not only be limited to the security industry. The current cameras have been deployed in the streets and alleys of the world, monitoring and recording around the clock. There are many valuable assets in a large amount of video data, and the development of intelligent video retrieval technology will be a weapon to tap the wealth of video data.
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In the past decade, DVR and DVS have made great progress in the digitization of the security industry. Especially in the past two years, with the advancement of the Safe City project, the streets of various cities have been covered with cameras. The continuous updating of storage technology has also accumulated huge amounts of video information for a large number of cases, which has greatly facilitated the cracking of cases. At this time, how to quickly extract valuable clues in the massive video becomes even more important. With the growing demand for security intelligence, video retrieval technology has also developed rapidly. This article will in-depth interpretation of intelligent video retrieval technology for everyone.