What Is the US Drone Policy?

there are 2 kinds of drones. those that drop bombs, and those that just observe. the kind that observes is no different than the police helicopter that prowls neighborhoods looking for criminals. that is the only "domestic" use that has been proposed. the policy concerning the other is this. the United States has declared war on terrorist organizations and is intent on tracking down and killing if necessary members of Al Qaeda. those drones carry bombs when a target has been found. those attacks happen in foreign countries with the permission of the host countries, it is considered a police action by them. since we have a large ground force in Afghanistan, those are primarily used by the military so that there is close coordination of forces. in other countries it is primarily the CIA since they have operatives on the ground there. 3 Americans have been killed because they were in the same tent as targeted Al Qaeda leaders, that was a risk they assumed on their own. another American was a target himself, having fled justice and arrest warrants. President Obama is proposing a closure to the war on terror, and that would include the use of drone attacks.

1. The simplest way to generate a drone note or chord on the Mac

I am guessing that there's probably a "web audio" project (meaning it's just a web page built with JavaScript) that can do it. But I see so many of them and do not bookmark them so I can not recommend anything more specific than googling webaudio tool or taking a look a Audiocrawl.co or browsing through similar lists: (1) (2) (3) (4). Other than that there are free programs similar to Band-in-a-box like Impro-Visor and MMA. I can not speak to how good they are because I use BIAB. On mobile, Chordbot is a decent BIAB-type app.With scoring software like Musescore (free) you could loop the playback of a measure or however long a phrase you need. Personally, I tend to use either a hardware looper (and can just loop guitar or bass), my DAW that is usually already open, or BIAB. But I understand the need for a lightweight solution and I would say a web page-if you can find one that meets your needs-is about as lightweight as you are going to get

2. Are you a drone,a clone, or alone?

I am the "one" united in all those choices.

3. Drone attacks - the act of a coward?

Attacking a weaker foe is the act of a coward and a bully. The US is bully to the world.

4. Which of you supports the wars in Iraq, Afghanistan and Libya and the new Drone attack on Iran?

INNOCENTS?...geezz...and what attack on Iran?when did this happen?

5. Drone video file size [A complete guide with real examples]

Capturing drone footage can be a pretty data-intensive process. From 4K videos and beautiful long time-lapse shots - not to mention the hundreds of photos you could end up taking - the storage of data has never been such a valuable resource. Here I want to share with you everything you need to know about drone video file size and the things you need to be aware of! I have REAL results from my experiment with one of my favorite drones - the DJI Mavic AIR... There is, of course, so much more that goes into determining what settings you should use to record your drone video. Here's the data that you will find most useful when making these choices. It's not as much as you may think! There's a simple rule of thumb based on the research below that you can use to work out how much data your drone video content will require if you are recording in the MP4 format. This data is collected from my drone and should be used as a guide for your drone's video size. You can see from the last column in the above table that as the video quality and frame rate decreases so does the amount of GB per minute of footage. There's another way that we can look at this data too. Let's say that you are in the market for a new memory card for your drone footage. What size memory card should you buy? I've taken the data collected and calculated how many minutes of footage you can get from a standard array of memory cards at different quality and frame rates. What size memory card should you buy for drone footage? If you are a hobby drone videographer you will probably not need more than 64 GB of memory - that is about 2.5 batteries worth of flying time for most commercial drones. However, if you are a professional drone company you will want a lot more storage on your memory car to make sure you have enough space for many multiples of flights. To get these numbers I ran an experiment with one of my favorite drones (it is small and powerful) the DJI Mavic Air. I recorded at a number of different quality and framerates - ones that are typically used by hobby and professional drone flyers. This was the outcome: The footage was collected on the internal storage of the DJI Mavic Air to overcome any issues in file write speed to an external SD card. The results suggest that this did not impact the I ran at least three recordings at different video lengths to be sure that there is no artifact relating to the length of the video in the data. This is what it looked like for each of my tests with the average of the results shown in the box below the table. Of these three video lengths tested with was the outcome: You will notice how much less the footage takes up on the storage. It is almost half despite being at 60 frames per second. I do not have need to record my footage in 4K - yes I know that it would be nice BUT it takes up so much more space than I need and I always export my videos in 1080 so it just seems a little counter intuitive. Here are the file sizes that I capture at different length videos and you will notice how much less per minute my footage takes up than the 4K equivalent! This is significantly lower than both the 4K and the 60 frames per second equivalent. I often choose to work with these setting as they are more than enough for my needs. So there we have it for my use case I use about 266 MB per minute of footage. That means that I can get 3 minutes and 42 seconds per GB of memory card space! You may have noticed that when you are recording long video formats on a drone the video will often be split up over two video files. That is not because of the drone but rather the FAT file system that the SD cards use. The 4 file size is a limit for the FAT32 file system which is what the SD cards use. If you want to avoid having the video spread over multiple shots you will either have to reduce the quality of the video so that you can get the total recording under 4Gb or you have to manually stop and start recording. To be honest, I've never had an issue with connecting two video files together in my video editor. One always seamlessly connects with the other. Maybe you want to reduce the file size of the video that you have recorded this next section is for you! Video size is dtermined by two important factors: Encoder - a device or software that enables video compression and/or decompression for digital video. Bit rate - A video bitrate is the number of "bits" that are processed in a unit of time. Video data rates are given in bits per second. The data rate for a video file is the bit rate. So a data rate specification for video content that runs at 1 megabyte per second would be given as a bitrate of 8 megabits per second (8 mbps). Commercial drones typically use MP4 and MOV export settings but the file name has NOTHING to do with the size of the exported video. It is the bitrate and sample rate that will determine the size of the file. Here some example file sizes and it's dependence on bit rate. Quite often we do not get a chance to choose the bitrate at which our drones record - or it can be too much of a pain to change mid flight. In that case you have a couple of options to choose from if you want a lower file size while flying. As we've seen from the above tables, the quality that you record in has a huge impact on the size of the file that you ultimately end up with and have to download to your computer. Choosing a quality that makes sence for your project is the only way that If you are exporting in 1080HD - there's probably no need to go to 4K. On the other hand, if your client is using the video for a multitude of purposes you may want to have the insurance of a 4K image. 3: Stop and start recording as you need to It can be tempting to push record at the very beginning of your flight. I know that quite often I even record the take off - just to be sure! However, if you want to reduce the drone video file size you may want to consider stopping and starting your drone footage as you are happy with the framing of the shot. This will save you a lot of space on your SD card and also make for easier editing when you come to import it into your favorite video editor!

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Introduction to 3D Reconstruction Technology of UAV Image Processing Technology
First, briefly introduce the process of three-dimensional reconstruction (SFM).1. Photo shootingIf you want to align with the map, the EXIF field of the collected image file needs to have GPS information or add the corresponding ground control point2. Extract feature pointsFeature points with certain invariance are extracted from photos. The feature points that can be found in multiple photos will be used for subsequent image matching and global model generation.The commonly used feature point extraction algorithms include sift, surf, orb, etc.3. Feature matchingPairwise matching can be performed, which will lead to the time complexity of N2.It can also be matched based on timing information or GPS position, which will significantly reduce the time consumption when there are many photos, but may lead to error accumulation.Photos that successfully match enough feature points will be considered as adjacent. A set of relative position relationships can be calculated between each pair of successfully matched images to represent how the camera needs to move from the shooting position of one image to the relative position of another image. Such motion can usually be expressed as a three-dimensional rotation matrix R and a displacement vector t. The rotation matrix can also be compactly represented by the unit quaternion.4. Optimization processTheoretically, if the matching relationship is a chain, the position of each point can be calculated directly. However, if the matching between photos is a "net" (a connected undirected graph in the data structure), the solution result of the camera position corresponding to each photo is not unique. Although the real camera position is unique, there will be errors due to multiple observations of the same camera position. Generally, it is assumed that the error term of the unknown distribution obeys the Gaussian distribution (the information entropy of the Gaussian distribution is the largest under the same variance), so the constructed three-dimensional point reduction non overlapping loss functions are all about the square of the distance. At this time, the optimization is similar to the structure of the spring net (the energy is proportional to the square of the error). If there is external position information, it can be understood that the spring net is fixedly connected to the building, so the optimal position is determined; If not, only the position between the "springs" has the optimal solution, and where the "spring net" is can be explained arbitrarily, which has nothing to do with the optimization process.The method to solve this optimization problem is to establish the optimization graph and construct the corresponding Jacobian matrix J and Hessian matrix H. Perform Gauss Newton or Levenberg – Marquardt descent. Here are some mathematical techniques such as turning a redundant rotating matrix (Lie group) into a non redundant vector (Lie algebra), but I won't introduce them more.After several drops, a result close to the optimal solution is generally obtained.5. Point cloud generationAfter optimization, the position of each photo camera and the spatial position corresponding to the feature point have been determined (note here that if the EXIF information of the photo does not have GPS position and GCP, the size of the object in the image is unknown. At this time, Se (3) transform degenerates into sim (3) transform). Sparse point clouds can be reconstructed, and the position of feature points can be restored to 3D space through triangulation.6. Point cloud densification and filteringThrough the coarse matching and coarse point cloud in the previous step, refine the part step by step, extract more features (not necessarily feature points, but also regional blocks), and match to obtain a more dense point cloud.Generally, there are only dozens to hundreds of sift / surf feature points in an image. This matching is very robust, but obviously even if all these points are matched, it is not enough to restore any valuable graphics. This requires the densification of the point cloud and the gradual refinement of the previous camera position and attitude information (hereinafter referred to as pose) to restore a more dense point cloud.Because it is local matching, even if the particularly robust algorithms such as sift and surf are not used, the impact of false matching is small. Patchmatching is generally used to match one area at a time. After this step, many three-dimensional vertices will be generated on the surface of the model. These vertices will appear in the final 3D model.In the process of feature point matching and point cloud densification, there will be many miscellaneous points that have nothing to do with the local model. These points are distributed at various positions in the three-dimensional space. If they are not removed, it will seriously affect the generation of rear patches (many large and strange shapes will be generated, so that the model cannot be viewed). Therefore, some filtering algorithms need to be used to filter out obviously wrong points. (for example, one or more points far away from the main building, isolated in the air, and points far away from other point groups in a large convex hull)7. Triangulation generation and patch refinementThrough the above operations, we have obtained a number of three-dimensional vertices ranging from tens of thousands to tens of millions (depending on the number and resolution of images, whether the size and texture of the scene are changeable, etc.). At this time, through Delaunay triangulation, a group of uniform triangles can be obtained, which will contain each vertex in the 3D graph. At this time, the surface structure of the scene will be clearly visible, but these faces have no color, only the vertices have color.At this time, the generated patch may be rough and contain more stray parts that do not belong to the object. Some refinement algorithms can be used to refine these patches to obtain a more reasonable model.8. Fill textureEach triangulation will correspond to a part of the original image. Cut these parts and paste them into the corresponding small triangles to obtain a more realistic three-dimensional model with color and texture. So far, the whole process of 3D restoration and reconstruction has been completed.
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