Camera tracking control method and device, equipment and medium

Abstract

The invention discloses a camera tracking control method and device, equipment and a medium, and the method comprises the steps: obtaining current environment sound data detected by a camera, carrying out the enhancement processing of the current environment sound data, and obtaining target environment sound data; determining target voice information and target position information corresponding to a to-be-tracked target object based on the target environment sound data; determining a target object image corresponding to a target object based on the target position information and a target environment image shot by the camera at the target position information; and controlling a camera to automatically track the target object according to the target position information and the target object image. Through the technical scheme of the embodiment of the invention, accurate and automatic tracking of the tracking object by the camera is realized, so that the labor cost can be reduced, the tracking control efficiency and accuracy can be improved, and the method and the device can adapt to complex and changeable environments and scenes.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a camera tracking control method, device, equipment and medium. Background Art

[0002] With the continuous advancement of sensor technology, signal processing technology, pattern recognition technology and artificial intelligence technology, the research on camera tracking control to achieve continuous and stable tracking of targets in complex environments has become increasingly important in practical significance.

[0003] At present, the traditional camera tracking control method is mainly implemented through manual intervention. For example, when tracking is required, the camera needs to be manually controlled through gestures or remote controls to select the tracking object. However, the traditional camera tracking control method has high labor costs, low tracking control efficiency and accuracy, and cannot adapt to complex and changing environments and scenes. Summary of the invention

[0004] The present invention provides a camera tracking control method, device, equipment and medium to achieve accurate and automatic tracking of a tracking object by a camera, thereby reducing labor costs, improving the efficiency and accuracy of tracking control, and being able to adapt to complex and changeable environments and scenes.

[0005] In a first aspect, an embodiment of the present invention provides a camera tracking control method, comprising:

[0006] Acquire current environmental sound data detected by the camera according to a preset period, and enhance the current environmental sound data to obtain target environmental sound data;

[0007] Based on the target environment sound data, determining target voice information and target position information corresponding to the target object to be tracked;

[0008] Determining a target object image corresponding to a target object based on the target location information and a target environment image captured by the camera at the target location information;

[0009] The camera is controlled to automatically track the target object according to the target position information and the target object image.

[0010] In a second aspect, an embodiment of the present invention further provides a camera tracking control device, comprising:

[0011] The ambient sound acquisition module is used to acquire the current ambient sound data detected by the camera according to a preset period, and enhance the current ambient sound data to obtain the target ambient sound data;

[0012] A position information acquisition module, used to determine the target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data;

[0013] A target image acquisition module, used to determine a target object image corresponding to the target object based on the target position information and a target environment image captured by the camera at the target position information;

[0014] The automatic tracking module is used to control the camera to automatically track the target object according to the target position information and the target object image.

[0015] In a third aspect, an embodiment of the present invention further provides an electronic device, characterized in that the electronic device comprises: at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the camera tracking control method provided by any embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute the camera tracking control method provided by any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention obtains the current environmental sound data detected by the camera through a preset period, and enhances the current environmental sound data to obtain the target environmental sound data, thereby improving the clarity of the sound data and providing a reliable basis for the subsequent extraction of target voice information. Based on the target environmental sound data, the target voice information and target position information corresponding to the target object to be tracked are determined, and the position of the target object can be tracked in real time, providing accurate guidance for the tracking of the camera. Based on the target position information and the target environmental image taken by the camera at the target position information, the target object image corresponding to the target object is determined, and rapid identification and extraction of the target object can be achieved. According to the target position information and the target object image, the camera is controlled to automatically track the target object, which can make full use of image information and improve the accuracy and reliability of the target object determination. By combining sound processing and image analysis technology, the camera can accurately and automatically track the tracking object, thereby reducing labor costs, improving the efficiency and accuracy of tracking control, and adapting to complex and changing environments and scenes.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a camera tracking control method provided according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of a camera tracking control method provided according to Embodiment 2 of the present invention;

[0024] Figure 3 is a structural schematic diagram of a camera tracking control device provided according to Embodiment 3 of the present invention;

[0025] Figure 4 is a structural schematic diagram of another camera tracking control device involved in Embodiment 3 of the present invention;

[0026] Figure 5 It is a structural schematic diagram of an electronic device for implementing the camera tracking control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "target", "current", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] Figure 1 A flowchart of a camera tracking control method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of automatically tracking a tracking object. Figure 1 As shown, the method can be performed by a camera tracking control device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method specifically comprises the following steps:

[0031] S110, obtaining current environmental sound data detected by the camera according to a preset period, and performing enhancement processing on the current environmental sound data to obtain target environmental sound data.

[0032] The camera may refer to a device for capturing and recording images and sounds. The current environment sound data may refer to the sound data collected in real time by the environment where the camera is located. These data are raw sound signals that have not been processed or have only been preliminarily preprocessed, and include various sound elements in the environment, such as human voice, mechanical sound, natural sound, etc. The target environment sound data may refer to the sound data obtained after enhancing the current environment sound data.

[0033] Specifically, through the built-in microphone of the camera or other audio acquisition equipment, the current environmental sound data corresponding to the environment in which the camera is located is obtained in real time, and the collected sound data is sound enhanced to obtain the target environmental sound data, thereby improving the signal-to-noise ratio and clarity of the sound data, which is convenient for subsequent further analysis of the sound data.

[0034] Exemplarily, "enhancing the current ambient sound data to obtain target ambient sound data" in S110 may include: filtering and denoising the current ambient sound data to obtain pre-processed current ambient sound data; performing signal enhancement processing on the pre-processed current ambient sound data to obtain target ambient sound data.

[0035] Specifically, the collected sound data is preprocessed, such as denoising, filtering, etc., to improve the signal-to-noise ratio of the sound data. A sound enhancement algorithm, such as adaptive gain control, noise suppression, etc., is used to enhance the preprocessed sound data to obtain the target environment sound data.

[0036] S120: Determine target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data.

[0037] The target object may refer to an individual or entity that the camera needs to track and identify. This object may be any entity that can appear in the camera's field of view, such as a person, an animal, or a vehicle. The target voice information may refer to the sound information related to the target object extracted from the ambient sound data collected by the camera. This information usually includes the voice content and voice features of the target object. The target position information may refer to the specific position information of the target object in the camera's field of view. This information is usually expressed in the form of coordinates, angles, or distances.

[0038] Specifically, the target environment sound data is subjected to speech recognition to determine the target object to be tracked, and the target speech information corresponding to the target object to be tracked is extracted. The sound source localization algorithm is used to determine the source position of the target speech information, i.e. the target position information, based on the characteristics of sound propagation, so that the position of the target object can be tracked in real time, providing precise guidance for the camera's tracking.

[0039] S130: Determine a target object image corresponding to the target object based on the target position information and the target environment image captured by the camera at the target position information.

[0040] The target environment image may refer to an image of the environment where the target object is located captured by the camera according to the target location information. The image usually includes the target object and its surrounding background information. The target object image may refer to an image portion corresponding to the target object extracted from the target environment image. This image usually only includes the target object itself, but not the surrounding background information.

[0041] Specifically, the camera adjusts the focal length and shooting angle according to the target location information, and captures the target environment image at the target location information, which can reflect the environment and state of the target object at a specific moment, and help understand the context information of the target object. Using image analysis algorithms, such as target detection and image segmentation, the target object image corresponding to the target object is extracted from the target environment image, thereby focusing on the target object itself, and providing clearer and more accurate visual information about the target object.

[0042] In this embodiment, the current environmental sound data is obtained according to a preset period, the current environmental sound data is enhanced to obtain the target environmental sound data, and the target voice information and target position information corresponding to the target object to be tracked are determined according to the corresponding target environmental sound data, that is, the corresponding target position information is also updated. When entering the tracking mode, if it is found that the current target position information and the previous target position information are significantly different, it means that the target object has been switched. At this time, the original target object is deleted, and then the pan-tilt head is rotated to the direction corresponding to the current target position information, and then the current target object is automatically tracked according to the current target object image.

[0043] Exemplarily, S130 may include: determining the distance between each object in the target environment image captured at the target location information and the target location information; and determining the image region where the object with the smallest distance is located as the target object image corresponding to the target object.

[0044] Specifically, in the target environment image, all objects are identified (this can be achieved through a target detection algorithm). Next, the spatial distance between each identified object and the target position information (usually a point or area) is calculated. This distance can be the pixel distance on the image plane, or it can be the actual physical distance after some transformation (such as camera calibration). After calculating the distance between all objects and the target position information, the object with the smallest distance is selected, and the image area occupied by the object is extracted as the target object image. By calculating the distance between the object and the target position information, it is possible to more accurately determine which object is closest to the target position, thereby excluding objects that do not match the target position information, reducing the possibility of misidentification, and extracting the correct target object image.

[0045] S140: Control a camera to automatically track the target object according to the target position information and the target object image.

[0046] Specifically, the target position information and the target object image are integrated, and the multimodal fusion algorithm is used to perform face recognition on the target object to determine the identity and characteristics of the target object, and the camera is controlled to automatically track the target object according to its position and movement trajectory. This embodiment can make full use of sound and image information through multimodal fusion to improve the accuracy and reliability of target object determination.

[0047] The technical solution of the embodiment of the present invention obtains the current environmental sound data detected by the camera through a preset period, and enhances the current environmental sound data to obtain the target environmental sound data, thereby improving the clarity of the sound data and providing a reliable basis for the subsequent extraction of target voice information. Based on the target environmental sound data, the target voice information and target position information corresponding to the target object to be tracked are determined, and the position of the target object can be tracked in real time, providing accurate guidance for the tracking of the camera. Based on the target position information and the target environmental image taken by the camera at the target position information, the target object image corresponding to the target object is determined, and the rapid identification and extraction of the target object can be achieved. According to the target position information and the target object image, the camera is controlled to automatically track the target object, which can make full use of the sound and image information and improve the accuracy and reliability of the target object determination. By combining sound processing and image analysis technology, the camera can accurately and automatically track the tracking object, thereby reducing labor costs, improving the efficiency and accuracy of tracking control, and adapting to complex and changing environments and scenes.

[0048] On the basis of the above solution, after S140, the method may further include: if it is detected that the speech interval of the target object is greater than the preset silence duration, then automatically tracking the target object is stopped.

[0049] The preset silence duration may refer to a preset sound interval time length.

[0050] Specifically, during the tracking process, voice detection is continuously performed on the ambient sound data collected by the camera to identify the voice activity of the target object. The silent period between the continuous voices of the target object, that is, the voice interval, is recorded. This interval refers to the length of time from when the target object stops speaking to when it starts speaking again. The system compares the calculated voice interval with a preset silence duration. If the detected voice interval is greater than the preset silence duration, it is considered that the target object may have left the tracking area or no longer needs to be tracked, so it is decided to stop the automatic tracking of the target object. By introducing a detection mechanism based on voice intervals to stop tracking during the automatic tracking process, it is possible to optimize resource utilization, reduce mistracking, improve user experience, and enhance system flexibility.

[0051] It should be noted that the target object can be a person. When entering the tracking mode, if it is found that there is a significant difference between the current direction of the human voice and the current tracking angle position, it means that the speaker has changed. At this time, the original target object is deleted, and then the camera is turned to the current direction of the human voice. Then, through the person object or face object in the image, reselect the tracking target. If there are multiple people, select the person who is more centered in the picture as the new target object and resume target tracking.

[0052] Embodiment 2

[0053] Figure 2 This is a flow chart of a camera tracking control method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes the step of "determining the target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data". The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here.

[0054] See also Figure 2 Another camera tracking control method provided in this embodiment specifically includes the following steps:

[0055] S210, obtaining current environmental sound data detected by the camera, and performing enhancement processing on the current environmental sound data to obtain target environmental sound data.

[0056] S220: Detect whether there is sound data of the object to be tracked in the target environment sound data.

[0057] The sound data of the object to be tracked may refer to sound data related to the target object (ie, the object to be tracked).

[0058] Specifically, feature extraction is performed on the target environment sound data, such as short-time energy, amplitude spectrum, zero-crossing rate, mel-spectrogram, etc. These features can reflect the time domain and frequency domain characteristics of the sound signal. The extracted features are matched with the preset sound feature library of the object to be tracked to determine whether the sound data of the object to be tracked exists in the target environment sound data, so that the sound of the object to be tracked can be accurately identified in the target environment sound data, providing a basis for subsequent processing.

[0059] S230: If there is sound data of the object to be tracked, determine target voice information corresponding to the target object to be tracked based on the sound data of the object to be tracked.

[0060] Specifically, after confirming the existence of the sound data of the object to be tracked, the sound data is segmented into continuous speech segments using sound segmentation technology. Speech recognition is performed on the segmented speech segments and converted into text information or speech feature vectors. These text information or feature vectors are the target speech information, which can accurately extract the sound information of the object to be tracked, providing an important basis for the subsequent determination and tracking of the target object.

[0061] Exemplarily, "determining the target voice information corresponding to the target object to be tracked based on the sound data of the target object to be tracked" in S230 may include: comparing the duration corresponding to the sound data of the target object to be tracked with a preset time threshold; if the duration corresponding to the sound data of the target object to be tracked is greater than the preset time threshold, then using the sound data of the target object to be tracked as the target voice information corresponding to the target object to be tracked.

[0062] Specifically, the collected sound data of the object to be tracked is processed and its duration is calculated. This usually involves segmenting the sound signal, detecting the voice activity within each segment, and accumulating the duration of these segments. The calculated duration of the sound data is compared with a preset time threshold. This preset time threshold is set according to the application scenario and actual needs, and is used to distinguish between meaningful sound data (i.e., target voice information) and background noise or short sound events. If the duration of the sound data is greater than the preset time threshold, it is regarded as the target voice information corresponding to the target object to be tracked. Short sound events and background noise can be filtered out, thereby more accurately determining the target voice information, which helps to reduce the occurrence of misidentification and mistracking.

[0063] S240: Position the target voice information and determine the target position information corresponding to the target object.

[0064] Specifically, the target voice information is located using a sound source localization algorithm, such as delay estimation, beamforming, etc. The target position information corresponding to the target object is calculated based on the time difference or phase difference of the sound signal reaching different microphones, and the position information of the target object can be determined in real time and accurately, providing precise guidance for camera tracking. Furthermore, due to the influence of factors such as environmental noise, the sound source localization result may have certain errors. Therefore, the localization result can be corrected to improve the accuracy of positioning.

[0065] Exemplarily, S240 may include: extracting features of the target voice information to obtain target voice features corresponding to the target voice information; and localizing the sound source based on the target voice features to determine target position information corresponding to the target object.

[0066] The target speech feature may refer to an acoustic feature extracted from the target speech information and capable of being used for sound source localization.

[0067] Specifically, the sound data that has been determined as the target voice information is processed to extract its unique acoustic features. These features may include spectral features, energy features, etc. Based on the extracted target voice features, a sound source localization algorithm is applied to determine the location of the sound source. For example, a sound source localization algorithm may include a method based on arrival time difference, a method based on beamforming, a method based on machine learning, etc. According to the output of the sound source localization algorithm, the target position information corresponding to the target object is determined. The target position information may be expressed in the form of coordinates (such as a point in a two-dimensional or three-dimensional space), or it may be expressed in terms of distance and direction relative to a reference point. Through feature extraction and sound source localization algorithms, accurate estimation of the position of the target object can be achieved, and real-time tracking and positioning of the target object can be achieved.

[0068] S250: Determine a target object image corresponding to the target object based on the target position information and the target environment image captured by the camera at the target position information.

[0069] S260: Control a camera to automatically track the target object according to the target position information and the target object image.

[0070] The technical solution of the embodiment of the present invention can accurately identify whether there is sound data of the object to be tracked in the target environment sound data by detecting whether there is sound data of the object to be tracked, providing a basis for subsequent processing. If there is sound data of the object to be tracked, the target voice information corresponding to the target object to be tracked is determined based on the sound data of the object to be tracked, and the sound information of the object to be tracked can be accurately extracted, providing an important basis for subsequent determination and tracking of the target object. The target voice information is located, and the target position information corresponding to the target object is determined, so that the position information of the target object can be determined in real time and accurately, providing precise guidance for the tracking of the camera. By detecting whether there is sound data of the object to be tracked in the target environment sound data, and determining the target voice information based on the sound data of the object to be tracked, and locating the target voice information to determine the target position information, accurate tracking and positioning of the target object can be achieved.

[0071] On the basis of the above solution, after S220, the method may further include: if the sound data of the object to be tracked does not exist in the target environment sound data, and there is no human image in the image captured by the camera, controlling the camera to enter a sleep state.

[0072] Specifically, voice recognition and feature matching technology can be used to detect whether there are sound features of the object to be tracked in the sound data of the target environment. If there are no sound features of the object to be tracked, proceed to the next step of judgment. Image processing technology, such as image recognition, edge detection, etc., is used to analyze the image taken by the camera. If no human image is detected in the image, that is, no human features or outlines are recognized, proceed to the next step. Based on the above judgment results, if there is no sound data of the object to be tracked in the sound data of the target environment and there is no human image in the image taken by the camera, the system believes that the current environment is safe or does not need to be monitored. At this time, the system sends a sleep command to the camera to control the camera to enter a low-power sleep state. Based on the dual detection of sound and image, it can more accurately determine whether the current environment needs to be monitored, thereby reducing false alarms and missed alarms, and protecting the privacy of users or scenes.

[0073] After S220, detecting whether there is sound data of the object to be tracked in the target environment sound data, and before S230, the method may further include: if there is sound data of the object to be tracked in the target environment sound data, and if the camera is in a dormant state, waking up the camera.

[0074] Specifically, the target environment sound data and the image captured by the camera are detected to determine whether there are sound features or human features of the object to be tracked. If there are sound features or human features of the object to be tracked, the current state of the camera is further checked. If the camera is currently in a dormant state, a wake-up operation is performed. By waking up the camera in time, it can be ensured that monitoring can be carried out immediately when the sound data of the object to be tracked is detected, thereby maintaining the continuity of monitoring. It should be noted that for a camera that enters privacy protection mode, that is, when its screen is covered or rotated to a specified position, its image is meaningless, and it can be awakened by voice at this time. Among them, privacy protection mode may refer to a specific functional state of a camera or camera, which is intended to protect the privacy and security of the user. When the camera enters privacy protection mode, its screen will be covered or rotated to a specified position, making the image content captured by the camera meaningless or unrecognizable.

[0075] Embodiment 3

[0076] Figure 3 This is a schematic diagram of the structure of a camera tracking control device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: an environmental sound acquisition module 310, a position information acquisition module 320, a target image acquisition module 330 and an automatic tracking module 340.

[0077] The ambient sound acquisition module 310 is used to acquire the current ambient sound data detected by the camera, and perform enhancement processing on the current ambient sound data to obtain the target ambient sound data;

[0078] A position information acquisition module 320 is used to determine target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data;

[0079] A target image acquisition module 330, configured to determine a target object image corresponding to the target object based on the target position information and a target environment image captured by the camera at the target position information;

[0080] The automatic tracking module 340 is used to control the camera to automatically track the target object according to the target position information and the target object image.

[0081] The technical solution of this embodiment obtains the current environmental sound data detected by the camera through a preset period, and enhances the current environmental sound data to obtain the target environmental sound data, thereby improving the clarity of the sound data and providing a reliable basis for the subsequent extraction of target voice information. Based on the target environmental sound data, the target voice information and target position information corresponding to the target object to be tracked are determined, and the position of the target object can be tracked in real time, providing accurate guidance for the tracking of the camera. Based on the target position information and the target environmental image captured by the camera at the target position information, the target object image corresponding to the target object is determined, and rapid identification and extraction of the target object can be achieved. According to the target position information and the target object image, the camera is controlled to automatically track the target object, which can make full use of sound and image information and improve the accuracy and reliability of the target object determination. By combining sound processing and image analysis technology, the camera can accurately and automatically track the tracking object, thereby reducing labor costs, improving the efficiency and accuracy of tracking control, and adapting to complex and changing environments and scenes.

[0082] Optionally, the ambient sound acquisition module 310 is specifically used to: filter and reduce noise on the current ambient sound data to obtain pre-processed current ambient sound data; perform signal enhancement processing on the pre-processed current ambient sound data to obtain target ambient sound data.

[0083] Alternatively, if Figure 4 As shown, the location information acquisition module 320 includes:

[0084] A tracking object detection unit 321 is used to detect whether there is sound data of the object to be tracked in the target environment sound data;

[0085] A voice information determining unit 322 is configured to determine target voice information corresponding to the target object to be tracked based on the sound data of the object to be tracked if there is sound data of the object to be tracked;

[0086] The position information determining unit 323 is used to locate the target voice information and determine the target position information corresponding to the target object.

[0087] Optionally, the voice information determination unit is specifically used to: compare the duration corresponding to the sound data of the object to be tracked with a preset time threshold; if the duration corresponding to the sound data of the object to be tracked is greater than the preset time threshold, then use the sound data of the object to be tracked as the target voice information corresponding to the target object to be tracked.

[0088] Optionally, the position information determination unit is specifically used to: perform feature extraction on the target voice information to obtain target voice features corresponding to the target voice information; perform sound source localization based on the target voice features to determine target position information corresponding to the target object.

[0089] Optionally, the target image acquisition module 330 is specifically used to: determine the distance between each object in the target environment image taken at the target location information and the target location information; and determine the image area where the object with the smallest distance is located as the target object image corresponding to the target object.

[0090] Alternatively, if Figure 4 As shown, the above device further includes: a sleep module 350;

[0091] The sleep module 350 is specifically used to control the camera to enter a sleep state if there is no sound data of the object to be tracked in the target environment sound data and there is no human image in the image taken by the camera.

[0092] Alternatively, if Figure 4 As shown, the above device also includes: a wake-up module 360;

[0093] The wake-up module 360 ​​is specifically configured to wake up the camera if the target environment sound data contains sound data of the object to be tracked and if the camera is in a dormant state.

[0094] The camera tracking control device provided in the embodiment of the present invention can execute the camera tracking control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Figure 5A schematic diagram of the structure of an electronic device 12 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as desktop computers, workstations, servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0096] like Figure 5 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0097] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0098] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0099] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0100] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0101] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0102] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing a camera tracking control method provided by the embodiment of the present invention, the method comprising:

[0103] Acquire current environmental sound data detected by the camera, and perform enhancement processing on the current environmental sound data to obtain target environmental sound data;

[0104] Based on the target environment sound data, determining target voice information and target position information corresponding to the target object to be tracked;

[0105] Determining a target object image corresponding to the target object based on the target location information and a target environment image captured by the camera at the target location information;

[0106] The camera is controlled to automatically track the target object according to the target position information and the target object image.

[0107] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the camera tracking control method provided by any embodiment of the present invention.

[0108] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the camera tracking control method provided in any embodiment of the present invention are implemented. The method includes:

[0109] Acquire current environmental sound data detected by the camera, and perform enhancement processing on the current environmental sound data to obtain target environmental sound data;

[0110] Based on the target environment sound data, determining target voice information and target position information corresponding to the target object to be tracked;

[0111] Determining a target object image corresponding to the target object based on the target location information and a target environment image captured by the camera at the target location information;

[0112] The camera is controlled to automatically track the target object according to the target position information and the target object image.

[0113] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0114] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0115] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0116] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0117] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0118] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A camera tracking control method, characterized in that: include: Acquire current environmental sound data detected by the camera according to a preset period, and enhance the current environmental sound data to obtain target environmental sound data; Based on the target environment sound data, determining target voice information and target position information corresponding to the target object to be tracked; Determining a target object image corresponding to a target object based on the target location information and a target environment image captured by the camera at the target location information; The camera is controlled to automatically track the target object according to the target position information and the target object image.

2. The method according to claim 1, characterized in that The step of performing enhancement processing on the current environmental sound data to obtain target environmental sound data includes: Performing filtering and noise reduction processing on the current environmental sound data to obtain pre-processed current environmental sound data; The preprocessed current environmental sound data is subjected to signal enhancement processing to obtain target environmental sound data.

3. The method according to claim 1, characterized in that The step of determining target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data includes: Detecting whether there is sound data of the object to be tracked in the target environment sound data; If there is sound data of the object to be tracked, determining target voice information corresponding to the target object to be tracked based on the sound data of the object to be tracked; The target voice information is located to determine the target position information corresponding to the target object.

4. The method according to claim 3, characterized in that The step of determining target voice information corresponding to the target object to be tracked based on the sound data of the object to be tracked includes: Comparing the duration corresponding to the sound data of the object to be tracked with a preset time threshold; If the duration corresponding to the sound data of the object to be tracked is greater than the preset time threshold, the sound data of the object to be tracked is used as the target voice information corresponding to the target object to be tracked.

5. The method according to claim 3, characterized in that: The step of locating the target voice information and determining the target position information corresponding to the target object includes: Extracting features of the target speech information to obtain target speech features corresponding to the target speech information; The sound source is localized based on the target speech feature to determine the target position information corresponding to the target object.

6. The method according to claim 1, characterized in that The step of determining a target object image corresponding to a target object based on the target location information and a target environment image captured by the camera at the target location information comprises: Determine the distance between each object in the target environment image captured at the target location information and the target location information; The image region where the object with the smallest distance is located is determined as the target object image corresponding to the target object.

7. The method according to claim 3, characterized in that After detecting whether there is sound data of the object to be tracked in the target environment sound data, the method further includes: If the target environment sound data does not contain the sound data of the object to be tracked, and the image captured by the camera does not contain a person image, the camera is controlled to enter a dormant state.

8. The method according to claim 3, characterized in that If there is sound data of the object to be tracked, before determining the target voice information corresponding to the target object to be tracked based on the sound data of the object to be tracked, the method further includes: If the camera is in sleep mode, wake it up.

9. A camera tracking control device, characterized in that: include: The ambient sound acquisition module is used to acquire the current ambient sound data detected by the camera according to a preset period, and enhance the current ambient sound data to obtain the target ambient sound data; A position information acquisition module, used to determine the target voice information and target position information corresponding to the target object to be tracked based on the target environment sound data; A target image acquisition module, used to determine a target object image corresponding to the target object based on the target position information and a target environment image captured by the camera at the target position information; The automatic tracking module is used to control the camera to automatically track the target object according to the target position information and the target object image.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the camera tracking control method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the camera tracking control method according to any one of claims 1 to 8 when executed.

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