Automatic photographing method and device, carrier and storage medium

Abstract

The invention relates to the technical field of automatic photographing, and discloses an automatic photographing method and device, a carrier and a storage medium, and the method comprises the steps: obtaining a plurality of candidate driving routes of the carrier from a departure place to a destination, determining a first object through which the carrier passes when the carrier drives along the candidate driving routes, and preliminarily recognizing a photographing object in the route; determining a time period suitable for shooting the first object, prior characteristics of weather conditions, a time period when the carrier travels to the area where the first object is located along the candidate driving route, and prediction characteristics of the weather conditions, and finding out a target first object without shooting conflicts according to a matching condition of the prior characteristics and the prediction characteristics. And obtaining a recommended driving route, and further screening shooting scenes suitable for shooting. And finally, according to the target recommended driving route selected by the user, the vehicle is controlled to drive, the personalized scene requirement of the user is met, the camera of the vehicle is utilized to shoot the target first object in the driving process, and it is ensured that the shooting quality requirement of the user can be met.

Description

Technical Field

[0001] This application relates to the technical field of automatic photographing, and in particular to an automatic photographing method, device, vehicle, and storage medium. Background Art

[0002] In the related art, the automatic photographing method of the automatic photographing function of a vehicle is that the vehicle travels to a photographing location preset by a user for photographing, and the vehicle needs to set a relatively large number of photographing locations by itself, so the convenience of the user of the vehicle using the automatic photographing function of the vehicle is poor. Summary of the Invention

[0003] In view of this, this application provides an automatic photographing method, device, vehicle, and storage medium to solve the problem of poor convenience in using the automatic photographing function of a traditional vehicle.

[0004] In a first aspect, this application provides an automatic photographing method, and the method includes:

[0005] Obtain multiple candidate driving routes of the vehicle from a starting point to a destination, and determine a first object for each candidate driving route, where the first object of the candidate driving route is an object in the area passed by the vehicle when traveling according to the candidate driving route;

[0006] According to the prior feature and predicted feature of the first object, find a recommended driving route from the candidate driving routes, where the recommended driving route has a target first object, and the prior feature of the target first object matches the predicted feature of the target first object. The prior feature of the first object indicates the time period suitable for photographing the first object and the weather condition suitable for photographing the first object, and the predicted feature of the first object indicates the time period when the vehicle is in the area where the first object is located when traveling according to the candidate driving route to which the first object belongs and the weather condition in the area during the time period when the vehicle is in the area where the first object is located;

[0007] Control the vehicle to travel according to the target recommended driving route selected by the user from the recommended driving routes, and when the vehicle is in the area where the target first object is located during the time period in the predicted feature of the target first object of the target recommended driving route, use the camera of the vehicle to photograph the target first object.

[0008] In the automatic photographing method provided by the embodiments of the present disclosure, multiple candidate driving routes of a vehicle from a departure place to a destination are obtained, and a first object passed by the vehicle when driving along the candidate driving routes is determined, and the photographing objects in the routes are initially identified. Then, the prior features of the time period suitable for photographing the first object and the weather condition, the predicted features of the time period when the vehicle drives along the candidate driving routes to reach the area where the first object is located and the weather condition are determined. According to the matching situation of the prior features and the predicted features, a target first object without photographing conflicts is found from the multiple candidate driving routes to obtain a recommended driving route, and the photographing scenes suitable for photographing are further screened. Finally, the vehicle is controlled to drive according to the target recommended driving route selected by the user to meet the personalized scene requirements of the user, and the first object is photographed by using the camera of the vehicle during the driving process to ensure that the time period and the weather condition when the vehicle reaches the area where the first object is located can meet the requirements of the user for high photographing quality. The photographed object, that is, the target first object, is automatically identified without the user of the vehicle setting a photographing location, which simplifies the operation of the user of the vehicle and improves the convenience of the user of the vehicle using the automatic photographing function of the vehicle, and improves the user experience of the user of the vehicle for the automatic photographing function of the vehicle. At the same time, photographing the target first object in the time period suitable for photographing the target first object and in the weather environment suitable for photographing the target first object makes the picture of the photographed target first object have a higher quality, and improves the user experience of the user of the vehicle for the automatic photographing function of the vehicle.

[0009] In an alternative embodiment, the prior features of the first object are from a prior feature set, and the prior feature set includes the prior features of each second object in a second object set; the method further includes:

[0010] For each second object in at least part of the second objects in the second object set, by using a trained photographing parameter prediction model, according to the information of the second object for obtaining the prior features, the prior features of the second object are obtained, and the information for obtaining the prior features includes at least part of the following items: the image of the second object, the position information of the second object, and the category of the second object.

[0011] Beneficial effects: The present application utilizes a trained photographing parameter prediction model in advance, and trains and learns the prior features such as the time period suitable for photographing the second object and the weather condition according to the image, position information, and category of the second object to construct a prior feature set, so as to quickly determine the prior features such as the time period suitable for photographing the first object in the candidate driving routes and the weather condition, so as to screen out the photographing objects with better photographing effects in combination with the predicted features of the first object, thereby meeting the photographing quality requirements of the user.

[0012] In an alternative embodiment, the prior features of the first object further indicate: the vehicle speed suitable for photographing the first object and the distance correlation information between the vehicle suitable for photographing the first object and the first object; controlling the vehicle to travel according to the target recommended travel route selected by the user includes:

[0013] Before controlling the vehicle to enter the area where the target first object is located during the suitable photographing time period of the target first object on the target recommended travel route, according to the distance correlation information, determine the target travel road for the target first object, and control the vehicle to travel on the target travel road for the target first object at the vehicle speed suitable for photographing the target first object.

[0014] Beneficial effects: Based on the target recommended travel route and the distance correlation information, this application controls the driving situation of the vehicle, adjusts the driving speed and travel road of the vehicle, ensures that the customer vehicle can reach the area where the target first object is located within the time period suitable for photographing the target first object, and travels at the vehicle speed suitable for photographing the target first object on the target travel road for the target first object, further improving the photographing quality.

[0015] In an alternative embodiment, the method further includes:

[0016] When it is determined that the vehicle cannot be in the area where the target first object is located within the time period of the predicted features of the target first object on the target recommended travel route, generate a new candidate driving route based on the current position and destination of the vehicle.

[0017] Beneficial effects: When this application determines that the vehicle cannot reach the area where the target first object is located within the time period of the predicted features of the target first object, a new candidate driving route is regenerated, avoiding the situation that the weather condition at the time when the vehicle arrives at the shooting scene no longer meets the suitable shooting weather condition, thereby preventing the impact on the shooting quality and being beneficial to improving the user experience.

[0018] In an alternative embodiment, photographing the target first object using the camera of the vehicle includes:

[0019] Determine the camera parameters for suitably photographing the target first object according to at least one of the time period suitable for photographing the first object, the weather condition suitable for photographing the first object, and the vehicle speed suitable for photographing the first object;

[0020] Using the camera of the vehicle, take a photo of the target first object according to the camera parameters for suitably photographing the target first object to obtain a photographed photo.

[0021] Beneficial effects: The present application adjusts the camera according to the vehicle speed, time period, and weather conditions suitable for photographing the target first object, and takes a photo of the target first object, which can further improve the shooting effect of the taken photo and meet the user's requirements for the shooting quality of the shooting scene.

[0022] In an alternative embodiment, after photographing the target first object using the vehicle's camera, the method further includes:

[0023] Generating a caption and / or background music based on the weather conditions suitable for photographing the target first object and / or user input information;

[0024] Generating a shooting file according to at least one of the taken photo, caption, and background music.

[0025] Beneficial effects: The present application generates a caption and / or background music for the taken photo based on the weather conditions and / or user input information, and presents the weather conditions and / or user input information in a diversified form combining pictures, texts, and music, thereby meeting the personalized needs of users.

[0026] In an alternative embodiment, the method further includes:

[0027] Responding to a user's adjustment instruction for the shooting file, modifying the shooting file, and sending the modified shooting file to the user.

[0028] Beneficial effects: The present application modifies the shooting file according to the user's adjustment instruction for the shooting file, making the generated shooting file more in line with the user's needs.

[0029] In a second aspect, the present application provides an automatic photographing device, which includes:

[0030] An acquisition module, configured to acquire multiple candidate driving routes of the vehicle from the departure place to the destination, and determine the first object of each candidate driving route, where the first object of the candidate driving route is an object within the area passed by the vehicle when following the candidate driving route;

[0031] A processing module, configured to find a recommended driving route from the candidate driving routes according to the prior features and predicted features of the first object, where the recommended driving route has a target first object, the prior features of the target first object match the predicted features of the target first object, the prior features of the first object indicate the time period suitable for photographing the first object and the weather conditions suitable for photographing the first object, and the predicted features of the first object indicate the time period when the vehicle is in the area where the first object is located when following the candidate driving route to which the first object belongs and the weather conditions in the area during the time period when the vehicle is in the area where the first object is located;

[0032] A control module, configured to control the vehicle to travel according to a target recommended driving route selected by a user from the recommended driving routes, and when the vehicle is within the area where the target first object is located during the time period in the predicted features of the target first object on the target recommended driving route, use the camera of the vehicle to photograph the target first object.

[0033] In a third aspect, the present application provides a vehicle, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the automatic photographing method according to the first aspect or any corresponding embodiment thereof.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the automatic photographing method according to the first aspect or any corresponding embodiment thereof. Description of the Drawings

[0035] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required to be used in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0036] Figure 1 It is a flowchart of the automatic photographing method according to an embodiment of the present application;

[0037] Figure 2 It is a flowchart of another automatic photographing method according to an embodiment of the present application;

[0038] Figure 3 It is a schematic diagram of a candidate driving route according to an embodiment of the present application;

[0039] Figure 4 It is a flowchart of yet another automatic photographing method according to an embodiment of the present application;

[0040] Figure 5 It is a flowchart of still another automatic photographing method according to an embodiment of the present application;

[0041] Figure 6 It is a block diagram of the structure of the automatic photographing device according to an embodiment of the present application;

[0042] Figure 7 It is a schematic diagram of the hardware structure of the vehicle according to an embodiment of the present application. Detailed Embodiments

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the protection scope of this application.

[0044] Currently, new types of vehicles such as new energy vehicles and intelligent driving vehicles have multiple cameras at different positions throughout the vehicle. Combining with the powerful in-vehicle computing function of current vehicles, more scenario applications can be realized, but they are mainly used for road condition detection, resulting in a situation of redundant function waste.

[0045] Existing vehicles mainly use dash cams for simple shooting, which cannot meet the customer's requirements for the shooting quality of the scenery along the way. Moreover, existing vehicle navigation only provides route navigation and does not accurately divide and identify the scenery along the way, resulting in the customer being unable to make good shooting preparations when suddenly encountering beautiful scenery during driving and missing the shooting opportunity. In addition, existing vehicles do not know the scenery status by the roadside under specific weather conditions and cannot ensure that the weather is suitable for taking pictures when the customer arrives at the corresponding scene. That is to say, as the scenarios of customers' driving and riding trips and Internet information sharing continue to increase, and the demand for shooting the scenery along the way during the driving process continues to increase, traditional vehicle shooting far from meets the customer's needs.

[0046] Therefore, the embodiments of this application provide an automatic photographing method. First, multiple candidate driving routes for the vehicle to travel from the departure place to the destination are obtained, and the first objects passed by the vehicle along the candidate driving routes are determined to initially identify the shooting scenarios in the driving routes. Then, the time periods and weather conditions suitable for shooting the first objects are determined, as well as the time periods and weather conditions when the vehicle travels along the candidate driving routes to the area where the first objects are located. According to the matching situation between the two, a recommended driving route is found from the multiple candidate driving routes, and the shooting scenarios suitable for shooting in terms of time periods and weather conditions are further screened out. Finally, the vehicle is controlled to travel according to the target recommended driving route selected by the user, and the camera of the vehicle is used to shoot the target first object during the driving process, meeting the user's personalized scenario requirements and ensuring that the time periods and weather conditions when the vehicle arrives at the area where the target first objects are located meet the user's shooting quality requirements.

[0047] According to the embodiments of this application, an embodiment of an automatic photographing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0048] In this embodiment, an automatic photographing method is provided. The vehicle with a photographing function involved in this solution covers various types of manned devices, including but not limited to various vehicles traveling on land, such as cars, buses, trucks, etc.; aircraft that can fly in the air, such as helicopters, small passenger planes, etc., and flying cars with both land travel and air flight capabilities; and also includes water vehicles sailing on water, such as yachts, ferries, etc. These vehicles can all apply the automatic photographing method provided by this solution. Figure 1 It is a flowchart of the automatic photographing method according to an embodiment of the present application, as Figure 1 shown, and this process includes the following steps:

[0049] Step S101, obtain multiple candidate driving routes of the vehicle from the departure place to the destination, and determine the first object of each candidate driving route, where the first object of the candidate driving route is an object in the area passed by the vehicle when following the candidate driving route.

[0050] Specifically, the vehicle performs path planning based on the departure place and destination given by the user to generate multiple candidate driving routes. Then, according to the navigation locations and routes of the candidate driving routes, the navigation driving time, and the weather changes during navigation, comprehensively screen the scenery visible to customers in the areas along the candidate driving routes, including plants, mountains, lakes, the sky, animals, etc. It is also possible to screen the shooting scenes according to the sharing information queried from the Internet or according to the scenery photographing elements.

[0051] Exemplarily, based on the input of the information of the departure place and destination, generate candidate driving routes, identify and screen the scenic spots in the candidate driving routes according to the Internet information. Part of the scenic spot screening is based on the scenic spots recorded on the network, and the other part is based on the map geographical information and the surrounding ecological information to identify the information of the surrounding vegetation, rivers, mountain roads, etc. on the candidate driving routes, so as to determine the first object of each candidate driving route. That is to say, the first object is not fixed to the scenic spots recorded on the network, and it is also possible to intelligently identify the shooting scenes in the route by combining the map geographical information, the surrounding ecological information, and the weather information, realizing mapless scenic spot prediction.

[0052] In the embodiment of the present application, for a first object, there is a road in the area where the first object is located that the vehicle passes through when following the candidate route to which the first object belongs. When the vehicle is in the area where the first object is located, the camera of the vehicle can photograph the first object.

[0053] In an optional implementation manner, the boundary of the area where the first object is located is preset. For example, taking the vehicle as an example, preset the boundaries of the areas where each shooting scene is located in the in-vehicle navigation map to facilitate the vehicle to more accurately define whether it has traveled to the area where the first object is located when following the corresponding route.

[0054] In another alternative implementation, an area centered at, for example, the geometric center point of the position of the first object and having a preset shape and a preset size is used as the area where the first object is located.

[0055] In some alternative embodiments, the customer can customize shooting scenes such as landscapes and locations according to requirements, and the vehicle updates and adjusts the navigation route, navigation time, etc. according to the corresponding customization requirements, so as to meet the customized requirements of the user for the shooting scene and the vehicle driving route as much as possible.

[0056] Step S102: According to the prior features and predicted features of the first object, find a recommended driving route from the candidate driving routes. Among them, the recommended driving route has a target first object, and the prior features of the target first object of the recommended driving route match the predicted features of the target first object. The prior features of the first object indicate the time period suitable for shooting the first object and the weather conditions suitable for shooting the first object. The predicted features of the first object indicate the time period when the vehicle is in the area where the first object is located when driving along the candidate driving route to which the first object belongs, and the weather conditions in the area during the time period when the vehicle is in the area where the first object is located.

[0057] For the first object j of the candidate driving route i, the prior features of the first object j indicate the time period suitable for shooting the first object j and the weather conditions suitable for shooting the first object j. The predicted features of the first object j indicate the time period when the vehicle is in the area where the first object j is located when driving along the candidate driving route i to which the first object j belongs, and the weather conditions in the area during this time period.

[0058] Among them, the candidate driving route i can be any one of the candidate routes, and the first object j is any one of the first objects of the candidate driving route i.

[0059] For the candidate driving route i, if at least some of the first objects of the candidate driving route i meet the matching condition, the candidate driving route i can be used as the recommended driving route.

[0060] Among them, the matching condition is that the prior features of the first object of the candidate driving route i match the predicted features of the first object of the candidate driving route i. Among them, the first object of the candidate driving route i that meets the matching condition is the target first object of the recommended driving route.

[0061] As an example, if the candidate driving route i is the recommended driving route, the prior features of the first object m of the candidate driving route i match the predicted features of the first object m of the candidate driving route i, and the first object m of the candidate driving route i is the target first object of the recommended driving route.

[0062] In some alternative embodiments, the candidate driving routes generally include the time periods for the vehicle to reach the areas where each first object is located. Therefore, the navigation information of the candidate driving routes can be directly extracted to obtain the time periods when the vehicle is in the areas where the first objects are located while driving along the candidate driving routes belonging to the first objects. Further, weather forecast data can be obtained to find the weather conditions in the areas where the first objects are located during the corresponding time periods, so as to obtain the predicted features of the first objects.

[0063] In some alternative embodiments, the prior features of the first object come from a prior feature set, and the prior feature set includes the prior features of each second object in a second object set. For each second object in at least some of the second objects in the second object set, using a trained shooting parameter prediction model, according to the information of the second object used to obtain the prior features, the prior features of the second object are obtained, and the information used to obtain the prior features includes at least some of the following items: the image of the second object, the location information of the second object, and the category of the second object.

[0064] Specifically, based on big picture data and shooting theory, in advance, the images, location information, and categories of shooting objects are obtained from Internet pictures and video inputs for training and learning, and a shooting parameter prediction model that can perform intelligent shooting on shooting scenes such as animals, plants, and natural scenery is generated. The characteristics of the shooting parameter prediction model are that it can identify the time periods suitable for shooting the first object (such as seasons, morning, morning, afternoon, evening, etc.), the weather conditions suitable for shooting the first object (such as sunny, rainy, snowy, etc.), the vehicle speed suitable for shooting the first object, the distance correlation information between the vehicle and the first object suitable for shooting the first object, the image parameters suitable for shooting the first object, the vehicle orientation suitable for shooting the first object, etc. Based on this information, the optimal shooting parameters for the scene can be determined.

[0065] In some alternative embodiments, by combining the prior features and the predicted features of the first object, it can be determined whether there are conflicts between the time periods and weather conditions when the vehicle drives to the areas where the first objects are located along the corresponding routes and the time periods and weather conditions suitable for shooting, and the target first objects without conflicts are screened out, so as to determine the recommended driving routes.

[0066] Exemplarily, for the first object of the candidate driving route, by combining the predicted time periods and weather conditions for driving to the area where the first object is located, the time periods in the prior features of the first object are matched with the predicted time periods. If they match, it is confirmed that the first object is a shootable scenic spot; otherwise, the scenic spot is deleted, and options for the recommended driving route are provided based on the screening results to support the customer to adjust and confirm according to the needs.

[0067] In this embodiment, a pre-trained shooting parameter prediction model is utilized in advance, and based on the image, location information, and category of the second object, prior features such as the time period suitable for shooting the second object and the weather conditions are trained and learned to construct a set of prior features, so as to quickly determine the prior features such as the time period and weather conditions suitable for shooting the first object in the candidate driving routes, and then screen out the shooting objects with better shooting effects in combination with the predicted features of the first object, thereby meeting the shooting quality requirements of the user.

[0068] Step S103: Control the vehicle to drive according to the target recommended driving route selected by the user from the recommended driving routes, and when the vehicle is within the area where the target first object is located during the time period in the predicted features of the target first object on the target recommended driving route, use the camera of the vehicle to shoot the target first object.

[0069] Specifically, there are multiple recommended driving routes. After determining the recommended driving routes, the vehicle displays them and shows the scene information included in the routes. The user can select one of the recommended driving routes as the target recommended driving route according to their own intention and feedback it to the vehicle. The vehicle will drive according to the target recommended driving route and control the camera to shoot the target first object when it is within the area where the target first object is located during the suitable shooting time period, thereby meeting the shooting quality requirements of the user.

[0070] The automatic photographing method provided in this embodiment obtains multiple candidate driving routes for the vehicle to travel from the departure place to the destination, determines the first objects passed by the vehicle when driving along the candidate driving routes, and initially identifies the shooting objects in the driving routes. Then, it determines the prior features of the time period and weather conditions suitable for shooting the first object, the predicted features of the time period and weather conditions when the vehicle drives along the candidate driving routes to reach the area where the first object is located, and according to the matching situation of the prior features and the predicted features, searches for the target first object without shooting conflicts from multiple candidate driving routes to obtain the recommended driving route, and further screens the suitable shooting scenes. Finally, it controls the vehicle to drive according to the target recommended driving route selected by the user to meet the personalized scene requirements of the user, and uses the camera of the vehicle to shoot the target first object during the driving process to ensure that the time period and weather conditions when the vehicle reaches the area where the target first object is located can meet the shooting quality requirements of the user.

[0071] Exemplarily, assume that a flying car needs to depart from point A with coordinates (x1, y1, z1) and head to point B with coordinates (x2, y2, z2). Through a path planning algorithm, multiple candidate flight routes such as routes R1, R2, R3, etc. are obtained. For route R1, using geographic information, its first object is determined to be a valley located at longitude and latitude (a1, b1) and altitude h1; the first object of route R2 is a landmark building at longitude and latitude (a2, b2) and altitude h2. The prior features of the first object are obtained from historical data and an image analysis model. For example, the prior features of the valley are: the suitable shooting time period is at time T1, and the suitable weather condition is sunny with wind force less than level 3. Through a real-time traffic and meteorological prediction model, as well as the expected departure time and speed of the flying car, predicted features are obtained. For example, if flying along route R1, the flying car is expected to be in the area where the valley is located at time T2 (T2 > T1), and the weather in this area is predicted to be sunny and the wind force is level 2 during this time period. According to the prior feature and predicted feature matching algorithm, a recommended flight route is selected from the candidate routes. For example, route R1 becomes one of the recommended routes because the prior features of the valley highly match the predicted features. After the user selects the target recommended route R1 from the recommended routes, the flight control system of the flying car controls the flying car to fly along route R1 according to a preset flight trajectory control algorithm. When the flying car determines through the global positioning system and inertial navigation system that it is in the area where valley V1 with longitude and latitude (a1, b1) and altitude h1 is located at time T2, the camera system carried by the flying car automatically takes pictures of the valley, which is the target first object, according to preset shooting parameters (such as aperture parameter, shutter speed, sensitivity).

[0072] In this embodiment, an automatic photographing method is provided. The vehicle with a photographing function involved in this solution covers various types of manned devices, including but not limited to various vehicles traveling on land, such as sedans, buses, trucks, etc.; aircraft capable of flying in the air, such as helicopters, small passenger planes, etc., and flying cars with both land travel and air flight capabilities; and also includes water vehicles sailing on water, such as yachts, ferries, etc. These vehicles can all apply the automatic photographing method provided by this solution. Figure 2 is a flowchart of the automatic photographing method according to an embodiment of the present application, as Figure 2 shown, this process includes the following steps:

[0073] Step S201, obtain multiple candidate driving routes of the vehicle from the departure place to the destination, and determine the first object of each candidate driving route, where the first object of the candidate driving route is an object in the area passed by the vehicle when following the candidate driving route. For details, please refer to Figure 1 the description of step S101 in the embodiment shown, and details will not be repeated here.

[0074] Step S202: Based on the prior features and predicted features of the first object, search for a recommended driving route from the candidate driving routes. Among them, the recommended driving route has the target first object, and the prior features of the target first object of the recommended driving route match the predicted features of the target first object. The prior features of the first object indicate the time period suitable for photographing the first object and the weather conditions suitable for photographing the first object. The predicted features of the first object indicate the time period when the vehicle is in the area where the first object is located when driving along the candidate driving route to which the first object belongs, and the weather conditions in the area during the time period when the vehicle is in the area where the first object is located. For details, please refer to Figure 1 the description of step S102 in the embodiment shown, which will not be elaborated here.

[0075] Step S203: Control the vehicle to drive according to the target recommended driving route selected by the user. When the vehicle is in the area where the target first object is located within the time period in the predicted features of the target first object of the target recommended driving route, use the camera of the vehicle to photograph the target first object.

[0076] In some optional embodiments, the prior features of the first object further indicate: the vehicle speed suitable for photographing the first object, the distance association information between the vehicle and the first object suitable for photographing the first object, and the image parameters suitable for photographing the first object. The above step S203 includes:

[0077] Step S2031: Before controlling the vehicle to enter the area where the target first object is located within the suitable photographing time period of the target first object of the target recommended driving route, determine the target driving road for the target first object according to the distance association information, and control the vehicle to drive on the target driving road for the target first object at the vehicle speed suitable for photographing the target first object.

[0078] Specifically, the driving speed of the vehicle and the shooting distance of the driving road will both affect the shooting effect. If the driving speed is too fast, the photographed photos may be blurred, and the shooting distance greatly affects the focal length of the camera. Therefore, based on the target recommended driving route and the distance association information, control the driving situation of the vehicle, adjust the driving speed, driving road and orientation of the vehicle, etc., to ensure that the customer vehicle can reach the area where the target first object is located within the time period suitable for photographing the target first object, and drive at the vehicle speed suitable for photographing the target first object on the target driving road for the target first object, further improving the shooting quality.

[0079] In some optional embodiments, when it is determined that the vehicle cannot be in the area where the target first object is located within the time period in the predicted features of the target first object of the target recommended driving route, generate a new candidate driving route based on the current position and destination of the vehicle.

[0080] Exemplarily, taking a vehicle as an example, if traffic jams, traffic accidents or other situations occur, resulting in the vehicle being unable to reach the area where the target first object is located within the predicted feature time period of the target first object, it will automatically return to the previous link and regenerate a new candidate driving route, so as to avoid the weather condition when the vehicle arrives at the shooting scene no longer meeting the suitable shooting weather condition and prevent the impact on the shooting quality.

[0081] Exemplarily, taking a flying car as an example, if unexpected meteorological conditions are encountered during the flight, such as strong convective cloud clusters appearing on the flight route, after analysis by the meteorological model, according to the current flight speed and direction, the flying car will not be able to reach the area (X1, Y1, Z1) where the target first object is located within the time period T1 - T2. At this time, taking the current position (X 0 , Y 0 , Z 0 ) of the flying car as the starting point and the destination (X1, Y1, Z1) as the end point, combining real-time meteorological data, air traffic control information (such as no-fly zones, positions and flight routes of other aircraft, etc.) and the performance parameters of the flying car itself (such as maximum flight speed, endurance, etc.), using the graph search algorithm, multiple new candidate flight routes are generated.

[0082] Step S2032, determine the camera parameters for appropriately photographing the target first object according to at least one of the time period suitable for photographing the first object, the weather condition suitable for photographing the first object, and the vehicle speed suitable for photographing the first object; use the camera of the vehicle to take a picture of the target first object according to the camera parameters for appropriately photographing the target first object to obtain a photographed picture.

[0083] Exemplarily, the light in the morning or evening is relatively soft and the colors are relatively rich, but the brightness may be low. Therefore, the sensitivity, shutter speed, aperture and other parameters of the camera can be appropriately adjusted to obtain better picture brightness, clarity, depth of field and picture quality. The specific settings of the camera parameters can be set according to the actual scene.

[0084] Exemplarily, on a sunny day, the light is sufficient and bright, and the camera can be set with a low ISO, a fast shutter speed and a small aperture; on a cloudy day, the light is soft but overall dark, so a higher ISO, a slower shutter speed and a medium to large aperture can be set. The specific parameter values can be set according to the actual scene.

[0085] Exemplarily, when the vehicle is moving at a low speed, it is relatively easy for the camera to capture a clear image, and the shutter speed can be relatively slow, so as to better freeze the image and reduce blurring; while when the vehicle is moving at a high speed, the shutter speed is relatively fast to prevent the photo from being blurred. A mapping relationship between the vehicle speed and the shutter speed can be established in advance so as to set the shutter speed of the camera based on the vehicle speed of the vehicle.

[0086] The present application adjusts the camera using the vehicle speed, time period, and weather conditions suitable for photographing the target first object, and takes a photo of the target first object, which can further improve the shooting effect of the taken photo and meet the shooting quality requirements of the user for the shooting scene.

[0087] In some alternative embodiments, a caption and / or background music is generated based on the weather conditions suitable for photographing the target first object and / or user input information. Then, a shooting file is generated according to the taken photo, caption, and / or background music. Exemplarily, if the weather conditions suitable for photographing the target first object are sunny, a lively and brisk background music can be selected, and a caption related to the weather conditions is automatically generated. And to meet the personalized needs of the user, the user can also input text information by himself / herself to form a caption and select the background music of the shooting file, so as to diversely present the weather conditions and / or the user input information in the form of a combination of pictures, texts, and music, and meet the personalized needs of the user.

[0088] In some alternative embodiments, in response to a user's adjustment instruction for the shooting file, the shooting file is modified, and the modified shooting file is sent to the user. For example, the customer puts forward adjustment opinions or issues confirmations for the generated shooting file. If modification is required, the shooting file is optimized and re-output to the customer for confirmation, so that the generated shooting file better meets the needs of the user.

[0089] In some alternative embodiments, the shooting file is processed to generate corresponding video pictures, which are passed to the customer for selection and confirmation. After confirmation, they are published on an Internet sharing platform to meet the sharing needs of the user. Further, the shooting file can also be scored based on the customer's selection results and the review results uploaded to the Internet, and imported into a database to continuously iterate and optimize the shooting parameter prediction model.

[0090] The automatic photographing method provided by the embodiments of the present application has a function of screening scenic spots on the route, which can be customized according to customer needs, meet the personalized customization needs of users, and make preparations for photographing in advance before driving to the corresponding scenic spots, thereby improving the shooting quality. At the same time, the vehicle speed, driving road, shooting layout, light, angle, etc. of the vehicle can be adjusted during shooting to improve the shooting effect. In addition, captions and / or background music can be compiled and published according to user input information such as date, journey purpose, mood, passengers, etc. and weather conditions, further meeting the user's Internet sharing needs.

[0091] Taking the vehicle as an example, a specific application example is used to illustrate the automatic photographing method of the present application in detail below.

[0092] As Figure 3 shown, a candidate driving route is generated according to the departure place 01 and the destination 03 of the vehicle navigation, and the first object 02 that can be photographed in the candidate driving route is screened. The first object can be a beautiful scenery location. As Figure 4 shown, the prior features of the first object are further obtained, such as the time period and weather conditions suitable for photographing the first object, the type of beautiful scenery, and a brief introduction to the beautiful scenery state in the current season, and the predicted features of the first object are obtained by using the navigation route and weather forecast data, such as the time period and weather conditions when the vehicle drives to the area where the first object is located along the candidate driving route. The prior features and predicted features of the first object are matched, the scenic spots on the route are screened according to the matching result, and a recommended driving route is generated for the customer to select, and the target recommended driving route selected by the user is obtained. Finally, the vehicle is controlled to drive along the target recommended driving route, and the photographing system is controlled to take pictures and process the pictures, generate a shooting file and upload and publish it. In addition, the evaluation score of the shooting file can be obtained to optimize the intelligent shooting module.

[0093] Specifically, as Figure 5 shown, by collecting Internet pictures and shooting tutorial information, a basic information library is built, and an intelligent model that can identify the prior features of the first object is trained through a big data pre-learning algorithm. The intelligent model can be built into the intelligent driving system of the vehicle to obtain a shooting parameter prediction model. The prior features can also include the vehicle speed, driving road, image parameters, etc. suitable for photographing animals, plants, and natural scenery around the navigation. The image parameters are used for the layout design, color application, and light adjustment of the camera, so as to refine the photo content of the scenes of animals, plants, and natural scenery photographed by the vehicle along the road.

[0094] Refer to again Figure 5For the recognition of the scenery along the way, real-time weather forecasts and navigation route conditions are received through Internet information, so as to determine the time period and weather conditions when the vehicle travels to the area where the first object is located, obtain the predicted characteristics of the first object, and input the corresponding data information into the intelligent model.

[0095] See again Figure 5 Again, the intelligent model screens the first object on the candidate driving route based on the prior characteristics and predicted characteristics of the first object to obtain the recommended driving route. Moreover, the customer can select and specify the beautiful scenery location according to their actual situation. The intelligent model further screens the recommended driving route according to the specified result and outputs the target recommended driving route.

[0096] See again Figure 5 During the driving process according to the recommended driving route, combined with the real-time weather update and the actual driving situation of the vehicle, the corresponding navigation information is updated to the intelligent model. The intelligent model judges whether it is necessary to correct the navigation information. If the current time period and weather conditions cannot meet the beautiful scenery shooting requirements, the navigation information is corrected and output to the intelligent driving system.

[0097] See again Figure 5 The vehicle intelligent driving system controls the vehicle speed, driving road and orientation according to the navigation information of the target recommended driving route and the actual road conditions, so as to ensure that the vehicle arrives at the corresponding area at the time period suitable for shooting the target first object, providing the best state for the in-vehicle equipment to shoot.

[0098] See again Figure 5 The intelligent model controls the parameters such as the focal length and aperture of each in-vehicle shooting device according to the actual vehicle conditions and weather conditions before arriving at the beautiful scenery location, and at the same time shoots the beautiful scenery. The shot data file is fed back to the intelligent model by the in-vehicle equipment.

[0099] See again Figure 5 The intelligent model optimizes the shooting data in terms of layout, color, light, etc. At the same time, according to the driving climate, weather, customer information, etc., corresponding background music and captions are generated and output for the customer to confirm. The customer puts forward adjustment opinions or publishes confirmation on the generated shooting file. If modification is required, the intelligent model optimizes the shooting file and outputs it to the customer for confirmation again.

[0100] The algorithm of the traditional automatic photo - taking system for cars generates a driving route based on information such as history, scenic spots, tourism, and internet celebrity check - in records on the internet, uses the in - vehicle system to match and generate the driving route and control the vehicle to drive, then uses the camera to capture and take photos, and the in - vehicle system organizes and generates video photos, which are uploaded to the network after customer confirmation. The traditional system algorithm can only generate a driving route based on the recorded information on the internet and cannot recognize the scenery that has not been recorded. The scenarios corresponding to in - vehicle intelligent photo - taking are more random and accidentally generated, and the scenario applicability is poor. Moreover, it can only simply identify whether there is scenic - spot information and cannot identify and screen according to other information strongly related to photo - taking such as time, climate, and weather. Therefore, it cannot ensure that the scenery is suitable for taking photos when the vehicle arrives at the scenic spot. Due to this defect in accuracy, it will convey misleading information to customers.

[0101] Compared with the algorithm of the traditional automatic photo - taking system for cars, through the intelligent internet - connected in - vehicle system, this application can comprehensively analyze the locations passed by the navigation route and the weather forecast, calculate which natural scenery and corresponding weather conditions will be encountered on the journey, so as to screen out suitable shooting scenarios.

[0102] This application can, through the intelligent internet - connected in - vehicle system, learn from the connected scenic - view photos and the scenic - view photos shared on the internet to complete the intelligent recognition pre - training of scenic - view photos. The intelligent driving system of this application can, through the pre - learning experience of scenic - view photos, the natural scenery on the journey, and the weather conditions, screen out the locations where it is possible to take scenic - view photos, and push the corresponding locations, allowing customers to identify and confirm in advance whether they pay attention to the scenery at the corresponding locations.

[0103] This application can control the speed of the vehicle at the shooting location, adjust the shooting light settings according to the weather conditions and orientation, and can, according to the pre - learning of scenic - view photos, perform scenic - layout and correction to ensure the shooting quality. This application can generate corresponding background music and captions according to the shooting results, time, venue, and customer mood and send them to the internet for sharing.

[0104] In this embodiment, an automatic photo - taking device is also provided. This device is used to implement the above - mentioned embodiment, and the parts that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0105] This embodiment provides an automatic photo - taking device, as Figure 6 shown, including:

[0106] An acquisition module 601 is configured to acquire multiple candidate driving routes of a vehicle from a starting point to a destination, and determine a first object for each candidate driving route, where the first object of a candidate driving route is an object within the area passed by the vehicle when traveling according to the candidate driving route;

[0107] A processing module 602 is configured to find a recommended driving route from the candidate driving routes according to the prior features and predicted features of the first object, where the recommended driving route has a target first object, and the prior features of the target first object match the predicted features of the target first object. The prior features of the first object indicate the time period suitable for photographing the first object and the weather conditions suitable for photographing the first object. The predicted features of the first object indicate the time period when the vehicle is in the area where the first object is located when traveling according to the candidate driving route to which the first object belongs, and the weather conditions in the area during the time period when the vehicle is in the area where the first object is located;

[0108] A control module 603 is configured to control the vehicle to travel according to the target recommended driving route selected by the user from the recommended driving routes, and when the vehicle is within the area where the target first object is located during the time period in the predicted features of the target first object of the target recommended driving route, use the camera of the vehicle to photograph the target first object.

[0109] In some alternative embodiments, the prior features of the first object are from a prior feature set, and the prior feature set includes the prior features of each second object in a second object set; the apparatus is further configured to:

[0110] For each second object in at least a part of the second objects in the second object set, use a trained shooting parameter prediction model to obtain the prior features of the second object according to the information for obtaining the prior features of the second object, where the information for obtaining the prior features includes at least a part of the following items: the image of the second object, the location information of the second object, and the category of the second object.

[0111] In some alternative embodiments, the prior features of the first object further indicate the vehicle speed suitable for photographing the first object and the distance association information between the vehicle and the first object suitable for photographing the first object; the control module 603 is further configured to:

[0112] Before controlling the vehicle to enter the area where the target first object is located during the suitable photographing time period of the target first object of the target recommended driving route, determine a target driving road for the target first object according to the distance association information, and control the vehicle to travel on the target driving road for the target first object at the vehicle speed suitable for photographing the target first object.

[0113] In some alternative embodiments, the apparatus is further configured to:

[0114] When it is determined that the vehicle cannot be in the area where the target first object is within the time period of the predicted features of the target first object on the target recommended driving route, a new candidate driving route is generated based on the current position and destination of the vehicle.

[0115] In some alternative embodiments, the control module 603 is further configured to:

[0116] Determine camera parameters for appropriately photographing the target first object according to at least one of the time period suitable for photographing the first object, the weather condition suitable for photographing the first object, and the vehicle speed suitable for photographing the first object;

[0117] Use the camera of the vehicle to take a photo of the target first object according to the camera parameters for appropriately photographing the target first object, and obtain a photographed photo.

[0118] In some alternative embodiments, the device is further configured to:

[0119] Generate a caption and / or background music based on the weather condition suitable for photographing the target first object and / or user input information;

[0120] Generate a photographed file according to at least one of the photographed photo, the caption, and the background music.

[0121] In some alternative embodiments, the device is further configured to:

[0122] In response to a user's adjustment instruction for the photographed file, modify the photographed file and send the modified photographed file to the user.

[0123] The further functional descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0124] The automatic photographing device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0125] This application embodiment also provides a vehicle having the above Figure 6 shown automatic photographing device.

[0126] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a vehicle provided by an alternative embodiment of this application. As Figure 7As shown, the vehicle includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the vehicle, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if needed, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple devices can be connected, and each device provides part of the necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Figure 7 Taking one processor 10 as an example in

[0127] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0128] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0129] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the vehicle, etc. In addition, the memory 20 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the vehicle through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0130] The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memories.

[0131] The vehicle further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 can be connected through a bus or other means. Figure 7Take the bus connection as an example.

[0132] The input device 30 can receive input digital or character information and generate key signal inputs related to the user settings and function controls of the vehicle, such as a touch screen, keypad, mouse, trackpad, touchpad, pointing stick, one or more mouse buttons, trackball, joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., LED), and a haptic feedback device (e.g., a vibration motor), etc. The above display device includes but is not limited to a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device can be a touch screen.

[0133] The embodiments of the present application also provide a computer-readable storage medium. The methods according to the embodiments of the present application can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented by downloading through a network the original computer code stored in a remote storage medium or a non-transitory machine-readable storage medium and to be stored in a local storage medium, so that the methods described herein can be stored as such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0134] A part of the present application can be applied as a computer program product, such as computer program instructions. When executed by a computer, through the operation of the computer, the methods and / or technical solutions according to the present application can be invoked or provided. Those skilled in the art should be able to understand that the forms of existence of computer program instructions in a computer-readable medium include but are not limited to source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include but are not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Herein, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0135] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An automatic photographing method, characterized in that: The method comprises: Acquire multiple candidate driving routes of the vehicle from a departure point to a destination, and determine a first object of each candidate driving route, wherein the first object of the candidate driving route is an object in an area that the vehicle passes through when following the candidate driving route; Find a recommended driving route from the candidate driving routes according to the prior features and the predicted features of the first object, wherein the recommended driving route has a target first object, the prior features of the target first object match the predicted features of the target first object, the prior features of the first object indicate: a time period suitable for photographing the first object and a weather condition suitable for photographing the first object, and the predicted features of the first object indicate: a time period when the vehicle is in an area where the first object is located when traveling along the candidate driving route to which the first object belongs, and the weather condition of the area during the time period when the vehicle is in the area where the first object is located; The vehicle is controlled to travel according to a target recommended driving route selected by a user from recommended driving routes, and the target first object is photographed using a camera of the vehicle when the vehicle is within an area where the target first object is located within a time period in a predicted feature of the target first object of the target recommended driving route.

2. The method according to claim 1, characterized in that The prior feature of the first object comes from a prior feature set, and the prior feature set includes the prior feature of each second object in the second object set; the method further includes: For each second object in at least part of the second objects in the second object set, a priori features of the second object are obtained based on information of the second object used to obtain the prior features using the trained shooting parameter prediction model, where the information used to obtain the prior features includes at least part of the following items: an image of the second object, location information of the second object, and a category of the second object.

3. The method according to claim 1, characterized in that The priori feature of the first object further indicates: a vehicle speed suitable for photographing the first object and distance association information between the vehicle and the first object suitable for photographing the first object; and controlling the vehicle to travel according to the target recommended driving route selected by the user from the recommended driving routes includes: Before controlling the vehicle to enter the area where the target first object is located within a time period suitable for photographing the target first object of the target recommended driving route, the target driving road for the target first object is determined based on the distance association information, and the vehicle is controlled to travel on the target driving road for the target first object at a vehicle speed suitable for photographing the target first object.

4. The method according to claim 3, characterized in that The method further comprises: When it is determined that the vehicle cannot be in the area where the target first object is within the time period in the predicted characteristics of the target first object of the target recommended driving route, a new candidate driving route is generated based on the current position of the vehicle and the destination.

5. The method according to claim 3, characterized in that: The method of photographing the first target object using a camera of the vehicle includes: Determining a camera parameter suitable for photographing the target first object according to at least one of a time period suitable for photographing the first object, a weather condition suitable for photographing the first object, and a vehicle speed suitable for photographing the first object; The target first object is photographed using the camera of the vehicle according to camera parameters suitable for photographing the target first object to obtain photographed photos.

6. The method according to claim 5, characterized in that After photographing the target first object using the camera of the vehicle, the method further includes: Generate text and / or music based on weather conditions suitable for photographing the first target object and / or user input information; A shooting file is generated according to at least one of the shot photo, the accompanying text, and the accompanying music.

7. The method according to claim 6, characterized in that The method further comprises: In response to the user's adjustment instruction for the shooting file, the shooting file is modified, and the modified shooting file is sent to the user.

8. An automatic photographing device, characterized in that: The device comprises: An acquisition module, used to acquire multiple candidate driving routes of the vehicle from the departure point to the destination, and determine the first object of each candidate driving route, wherein the first object of the candidate driving route is an object in an area passed by the vehicle when following the candidate driving route; a processing module, configured to find a recommended driving route from candidate driving routes according to a priori features and predicted features of a first object, wherein the recommended driving route has a target first object, the priori features of the target first object match the predicted features of the target first object, the priori features of the first object indicate: a time period suitable for photographing the first object and a weather condition suitable for photographing the first object, and the predicted features of the first object indicate: a time period when the vehicle is in an area where the first object is located when traveling along the candidate driving route to which the first object belongs and the weather condition of the area during the time period when the vehicle is in the area where the first object is located; The control module is used to control the vehicle to travel according to the target recommended driving route selected by the user from the recommended driving routes, and to use the vehicle's camera to photograph the target first object when the vehicle is in an area where the target first object is located within a time period in the predicted characteristics of the target first object of the target recommended driving route.

9. A carrier, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the automatic photography method according to any one of claims 1 to 7 by executing the computer instructions.

10. 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 computer to execute the automatic photography method according to any one of claims 1 to 7.

Images