Universal Precautions under OSHA Bloodborne Pathogens regulations.
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As such, proceeding to check vitals of a very bloody mess as Crooks was immediately without gloves, and then immediately after putting your gloves on. Am I wrong in finding this a little odd?
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Here are the 8 casings, all positioned west of the shooter. 5 on the north side and 3 on the south side of the AGR6 roof.
As far as I know Michel was always standing east or north of the shooter. Maybe I missed something, but if you have any evidence that she planted something like 3 extra casings on the roof it would be highly appreciated you would share that information.
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It may not have come to her immediately to don her PPE, realizing she better do so after taking the vitals and having her hands close to or in contact with his blood. When Iâm working in my garage, I typically remember to put safety glasses on after I get sawdust or something in my eye. Thatâs my take on it.
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If the above spent casing animation is true fact,
they are being ejected slightly forwards and to the right.
Most Ar15âs eject in the yellow arrows arc below
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Oh, for crying out loud! How can the sun, when itâs off to the west, make that âbroken windowâ or âplexiglass filmâ appearance in a window thatâs facing south - from a person thatâs almost due south of said window? The windows you are showing in the first shot are clearly showing sun glare. Not even close to the broken window effect.
And yes, the second picture you show is clearly a reflection of a barn. A reflection with SKY and a TREE at the top, unlike any of the weird screenshots from Dave Stewartâs video. Those all have red all the way to the top of the window, even when taken from a camera/phone thatâs clearly almost at ground level.
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I made that gif out of screenshots from the Mike DiFrischa video (TMZ). If they didnât manipulate the footage then itâs true fact. Shell ejection at the exact moment of the first shot.
I assume for the first 3 shots he leand a little bit over the roof ridge and than moved back slightly to release shot 4-8. That might explain why 3 casings on the south and 5 on the north side of the roof.
I recall the discussion were the TMZ video was 'enhanced" from the original which then showed the spent shell & recoil; If they didnât manipulate the footage then itâs likely showing true fact.
Crooks exposure at 2nd shot, looks like to bottom of hair line exposed and top of torso based on shooting posture and magazine clearance issues, will need a graphic to determine minimum distance from ridgeline.
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Didnât see this one yet. Do you have a link to the video?
Thx for the link.
Itâs hard to tell quality isnât good enough and the roof too far away.
This is from the Dayve Stewert video, about 1sec before the first shot. You can clearly see the rifle and I would assume the rifle barrel goes quite a bite beyond the ridge line. But from this angle itâs hard to tell.
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Dried blood during a pulse check is low threat, plus a faint pulse reading would be challenging with latex gloves. I see no issues here.
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Thereâs no other plausible explanation for red reflection. If there was some unique new covert glass as proposed, think about it. It would not be RED. Wouldnât that defeat the covert purpose?? Plus why would we only see it in a few, extreme angle, images??
The white is obviously the clouds or the white barn roof. The white LED light is probably the SUV headlight facing the AGR. These old windows show glass waves imperfections. Lots of old windows do this. Not unusual. Go outside and look around the world.
NOT complicated stuff. This isnât a challenging observation.
Furthermore as repeatedly been pointed out, there was inadequate time to remove a window, shoot, and replace it without the 10-20 observers seeing it. Or it being obvious on film.
And thereâs obviously no shooting solution from the windows to Trump. Too many undeniable obstacles.
So the window theory is far too impossible and the windows are merely showing reflections.
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Notice in this image immediately before the shooting, cop is standing directly in front of obviously closed windows 1 and 2. Heâs facing and walking towards window 3. He would easily observe anyone removing windows. Yet another piece of evidence no shots fire from 3 closed windows.
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it is a business decision that relates to the personal health and safety of the care provider.
I can totally understand if she checked his vitals with her bare hand, because you simply feel much better whether there is a pulse or notâŚ
just like you have a much better trigger feeling with your bare trigger finger than when you are wearing a gloveâŚ
in the context of a first responder, gloves are worn to prevent any potentially harmful pathogens from being transmitted, and it is indeed very possible that she was on autopilot and checked the vitals glove-free first and then put them on to further evaluate crooks
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this is a great scheme!
Hi guys. I will present my final study of the geolocations of all points of interest. Since my last update I develop a method to convert pixels in a specific footage and covert to line of sights of objects that is possible to identify in the Google earth satellite picture. The method result is a grid-map off medium and maximum deviation of the horizontal position in pixels. The location with minimum maximum or minimum medium tends to be the best geolocation of footage.
The method has its limits because it is necessary to know where the horizon is in the footage so vertical lines can be located on the object to measure the horizontal distance in pixels.
In total I used 13 footages and 43 screen shots.
This study was based on minimizing the error of geolocations. To minimize the error the best reference points are light poles, visible edges of buildings, visible tree trunk, projected edges of buildings, projected trunk of trees.
Geolocation of light poles:
The best way to find the geolocation of light poles is to draw lines of shadow and the light pole, the point where it cross is the geolocation of base of light pole. here is an example of that:
Elevated position correction:
Reference points that are in elevated position must be corrected since the satellite picture is not perfectly vertical, but at angle of around 25 degrees in the case of 11/05/2021. This angle results in altering the geolocation of elevated position to the West, so the correction must be in the opposite direction to the East. For example, the frontal wall building 6 has 3m of elevation that in the satellite picture results in a dislocation of that position 1.4m to West. So, when defining any reference point on that wall the geolocation must be corrected 1.4m to East.
Using a drone footage of that wall I projected that image on Google Earth on the front of the building. So, when I need a geolocation of any point on that wall, I use this image to geolocate.
Observe that the West end of the building does not coincide with the roof image, also that difference will occur on any point on that wall.
Now the order of the footages will be important since some of them are more precise than others. The most precise one is RSBN, because the angle of the camera is wide, the footage is close to horizontal, and is Almost a still position. I used 2 methods to geolocated RSBN.
method 1: footage pixel model
For RSBN I used 5 different print screens of different times that covers different angles. Then I estimate the geolocation of each footage. Here is the map with all the reference points for RSBN.
The resulted geolcation of each image differ in around 2m. So, what I did I find the minimum error between all footages and the best geolocation found was here:
This grid is 3x3m pointed to the North and the middle is a reference point (586684.00; 4523384.00)
Also, I was able to find the angle of the camera without zoom of 70 degrees +/- 0.2 degree.
Result RSBN: 586684.48; 4523383.68
method 2: drone image.
This drone image has a lot of error, to minimize that I found points of references that are close to RSBN.
Drone photo:
Drone photo orientation: North: 40.857441°, East: -79.970249°, South: 40.856761°, West: -79.971883°, Rotation: -23.2355°
Here are the 3 points of references used on the zoomed image close to RSBN:
Here are the same points of references used on the satellite picture:
Here is RSBN location (method 1) on the RSBN podium of the drone image.
The error from method 1 and 2 is around 0.3m. Since the method 2 depends on defining where the camera is in the RSBN podium, method 1 is more reliable.
NTD and C3P:
With the line of sight of RSBN on NTD fottage, it reduces the points of tests for NTD locations. The same happens to C3P footage.
NTD sees RSBN at 11:56:
C3P sees RSBN and possible sees NTD at 1:27.
C3P lines of sight of RSBN and NTD in yellow and NTD lines of sight of RSBN in purple.
Also, after having RSBN NTD and C3P I was able to project lines of sight from Trump, James, David, the Bleacher top positions and the Teleprompter positions. This is all done without the drone image from the Trump podium.
The Trump podium top drone photo:
This photo has some distortion that are difficult to overcome. But a manage to use the perspective correction from PowerPoint and achieved some pretty good results.
Here is the perspective correction used on PowerPoint:
Rotation X: 358°; Rotation Y: 19°; Rotation Z: 359° perspective: 20°
And here is the orientation: North: 40.857287°, East: -79.970452°, South: 40.856745°, West: -79.971403°, Rotation: -23.5482°
Here are some the points I was able to identify.
The error was reduced from 1.5m to 0.3m. Now even the Barns are parallel to the satellite image and the level of accuracy is very high been possible to identify small variations on the roads.
Elevated positions corrections:
Now comes the correction of elevated positions on that image. Crossing all possible vertical lines, I found the most probable geolocation of the drone (586719.64; 4523375.42) and its elevation of 119m. Since the white tents have the same height, I was able to estimate corrections of elevated positions. The final result came pretty close the geolocation of bleachers using the footage method 1 with errors of less then 0.3m.
Here is the Bleachers corrected in blue.
The most distorted is the Middle bleacher.
Source 5:
This source is far away from the podium and since it is zoom in (only 5 degrees of angle of view) the geolocation from the pixel method is imprecise and the range can differ 1 meter to side and 5 meters to front and back. Still here is the geolocation (586658.66; 4523405.68) and the grid of error map projected on Google Earth.
James and David positions was checked by RSBN NTD, source 5 and TMX.
With the defined position of James I used James footage to validate his location and Trump location. It differs around 0.2m, but James could have moved to the side on the footage.
Middle bleacher footage that sees Dstew was synchronized with Dstew footage. This way I was able to identify Dstew line of sight in two times: at 1st shot and at the time Dstew sees Crooks seconds before shooting.
Synchronized footages when Dstew sees Crooks seconds before shooting:
Dstew footage was located during his movement during the shooting using the Middle bleacher footage, his on footage and some line of sights. Also his movement was considered linear during 1 and 4 shots.
The same method was applied to source 4.
Ross location was determined by his on footage and by source 4 seen him near shot 10.
Using Ross footage and Dstew Crooks position was determined by the line of sights from the footages. This was compared to the geolocation of Crooks using post images of the scene and the correction of the roof elevated position the locations differ around 0.2m.
The BWC footages was used to define the South Barn Snipper position by 2 print screens and the 9th shot snipper I used 2 prints also.
Here is the final result for all points of interest:
| ref | E (m) | N (m) |
|---|---|---|
| RSBN_V3 | 586684.48 | 4523383.68 |
| NTD | 586691.16 | 4523403.54 |
| c3p | 586733.45 | 4523409.60 |
| DRONE_STAGE1_height_119m | 586719.64 | 4523375.42 |
| Corey | 586736.21 | 4523417.70 |
| S5 | 586658.66 | 4523405.68 |
| James_v3 | 586722.04 | 4523372.12 |
| David_v3 | 586719.97 | 4523371.22 |
| Trump_v2 | 586726.82 | 4523394.08 |
| Trump_MIC | 586726.64 | 4523394.28 |
| SBlower | 586722.47 | 4523376.15 |
| TMX_v2 | 586740.37 | 4523498.02 |
| MB_N | 586744.48 | 4523394.30 |
| Dstew@1shoot | 586774.15 | 4523486.16 |
| Dstew@2shoot | 586775.89 | 4523486.19 |
| Dstew@3shoot | 586779.50 | 4523486.33 |
| Dstew@4to9shoot_V2 | 586781.91 | 4523486.56 |
| Dstew@10shoot | 586775.11 | 4523488.07 |
| source4@1shoot | 586693.00 | 4523528.92 |
| source4@2shoot | 586691.84 | 4523529.60 |
| source4@3shoot | 586690.60 | 4523530.21 |
| source4@4shoot | 586683.23 | 4523537.98 |
| source4@9shoot | 586682.84 | 4523539.08 |
| source4@10shoot | 586683.83 | 4523544.57 |
| Ross | 586683.91 | 4523542.97 |
| Crooks | 586767.73 | 4523529.40 |
| SB_Snipper 2 | 586763.45 | 4523360.11 |
| SB_Snipper 1 | 586762.39 | 4523360.54 |
| Snipper Shot 9 | 586761.86 | 4523426.72 |
| Cruizer | 586793.39 | 4523525.12 |
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