Thumbnail

Camera Device

How to add the Camera Device robot skill

  1. Load the most recent release of ARC (Get ARC).
  2. Press the Project tab from the top menu bar in ARC.
  3. Press Add Robot Skill from the button ribbon bar in ARC.
  4. Choose the Camera category tab.
  5. Press the Camera Device icon to add the robot skill to your project.

Don't have a robot yet?

Follow the Getting Started Guide to build a robot and use the Camera Device robot skill.


How to use the Camera Device robot skill

This skill uses any camera installed on your PC or robot to combine computer vision tracking with movement and data acquisition. Computer vision is an experimental technology that requires a clean and bright environment to detect objects and colors accurately. If a camera is mounted on your robot, you can use this skill to track color objects, motion, human faces, or view the camera image. The attributes of the detected image can be adjusted manually in this skill to remove any false positives. Test in a bright room and change the image attributes until the desired object/thing is solidly detected.

*Note: The included video tutorials are a little dated due to ARC's rapidly evolving interface and features. You should be able to extract the necessary tracking information within the videos even though the interface may not be identical to ARC today. :)



There are many sections on this page; here are some shortcuts:


Main Window - Device



This camera device is connected or built into your computer or robot. It can be an integrated webcam, USB, serial, wireless, etc.

Additional camera devices may be selected or entered when the camera is stopped (not running). If the EZB supports video, the robot skill will display the IP Address and any other USB or local cameras. The camera robot skill will also display cameras for other supported robots, such as the AR Parrot Drone. Additionally, you may manually enter a JPEG Snapshot HTTP address.

USB Camera Device - Clicking on the video device list will display USB cameras and capture devices. Select the USB device to use.

EZB Camera Device - If the EZB supports a video stream, the syntax for connecting to EZB cameras is EZB://192.168.0.1 or EZB://192.168.0.1:24 (if the port is specified). The type of EZBs that support video for this syntax is ESP32, EZ-B v4, IoTiny, Raspberry Pi, etc..

COM (UART) Device - If a camera is connected via a USB COM UART adapter, the port will be displayed in the dropdown. The syntax will be COMx (i.e., COM1, COM2, and so on). The default baud rate will be 3,333,333 if only the com port is selected. However, if the camera uses a different baud rate, it can be specified next to the com port with a: separator. Such as COM1:9600

Custom - This option allows the camera device robot skill to be in slave mode. It allows other robot skills to push video data to this robot skill. Some robot skills, such as the AR Parrot Drone, Intel Realsense, and Stream All The Video Sources will use this option.

JPEG Snapshot HTTP Video Device - a camera or video source that provides JPEG images may be selected as a camera device. Enter the complete HTTP URL of the video source. If the HTTP video source requires authentication, consult your device's documentation for the correct syntax. You may test the JPEG URL in a web browser to verify that it is valid and that only the JPEG is displayed, not any HTML. Example: http://192.168.100.2/cgi-bin/snapshot.cgi or http://192.168.100.2/image.jpg, etc..



1. Full Screen/Restore Button
This button makes the Camera Device skill full screen and restores it to its original size.

2. Camera Image Display
This section displays the Camera image, which the Image attributes sliders can manipulate.

3. Processed Image Drop-down
This dropdown allows you to select if the displayed image is processed (attributes manipulated) or original.

4. Pause detection Checkbox
Once checked, this checkbox stops the detection until unchecked.

5. Hide Settings Checkbox
Once checked, this checkbox makes the camera image fill up the camera skill; the option on the right side is hidden.

6. Tracking Frame Count
This displays how many frames per second are being tracked.

7. Refresh Button
This button refreshes the camera device list. It adds newly installed cameras to the list and removes unplugged devices.

8. Camera Device Drop-down
This dropdown lists the available camera devices that the camera device can use.

9. Network Scan Button
This button finds a camera on the network to which ARC is connected.

10. Resolution Drop-down
This dropdown allows you to select the resolution of your camera. You have the wrong resolution if your camera image doesn't appear when you click the Start/Stop button.

11. Start/Stop Button
This button will begin or end the camera image display from the selected camera device.

12. Reset Button
This button resets the changes to the image adjustment sliders.

13. Image Adjustment Sliders
These sliders adjust three different attributes of the camera image (Brightness, Contrast, and Saturation).

14. Start/Stop & Pause/Resume Video Recording Buttons
These buttons begin/end or pause/resume video recording from the active camera device. The video is recorded in .wmv format and is saved in your "\Pictures\My Robot Pictures" folder.

15. Sharpen Image Checkbox
This checkbox will sharpen the camera image. The image will have less blur and look crisper.

Main Window - Tracking



A tracking type is a function of what to recognize for tracking. For example, you would only select the Color tracking type to track the color RED. Each tracking type has configuration settings that are on its tabs. If you have Color checked as a tracking type, then the configuration for the Color tracking type is found in the tab labeled Color.

1. Tracking Type Checkboxes
These checkboxes will turn the different tracking types on/off. You can track multiple types simultaneously, but it's not often used this way.


Main Window - Color Tracking



This will track the specified predefined color from the Color tab. You can select the color between Red, Green, or Blue. The Color tab will also give you settings to adjust the brightness and size of the object. Hold the object in front of the camera while changing the settings. This is the basic color tracking method used in RoboScratch's "wait for color."

1. Detection Boxes
These boxes show where the selected color is detected on the camera image.

2. Color Drop-down
This dropdown gives you the selection of 3 colors (Red, Green, and Blue).

3. Minimum Object Size Slider
This slider allows you to select how large the detected colored object size must be before registering as a detection.

4. Example Minimum Size Display
This display gives you a visual reference of how large (in pixel size) the detected object will have to be in the camera image display.

5. Object Brightness Slider
This slider will adjust the brightness of the detected color. Adjust until only the desired object is detected.



Main Window - QR Code Tracking



You can use this tracking type to detect pre-encoded QR codes or the QR Code Generator (Add Skill -> Camera -> QR Code Encoder) to create your QR Codes and print them out. QR Code Tracking will detect QR codes, set the $CameraQRCode variable, or execute the code within the QR Code. Remember that QR Code recognition is CPU intensive and, therefore, slow. We do not recommend using QR codes for tracking. It is best used for identification and triggering events, not movement tracking. Note that the QR Code tracking type has additional settings in the Camera Device Settings.

1. QR code Detection Output
This is where the detected output from the QR code will be displayed.

2. QR Code
This QR code will be detected on the camera image display.

3. QR Code Checkbox
This checkbox will need to be enabled to track QR codes.

4. Camera Frame Rate
This displays the camera frame rate per second (fps) and the number of skipped frames.

Main Window - Multi Color Tracking



This is an advanced and more detailed tracking method over the generic Color tracking type. With Multi-Color, you can specify and fine-tune your color and add multiple colors. The camera robot skill will configure an ez-script variable to hold the name of the current detected color that has been detected. The multi-color definitions can be trained in the Multi-Color tab. If you name a custom color "Red," this does not override the basic predefined color tracking types. Basic color tracking (discussed above) has three predefined colors. This multicolor tracking type is separate and has no relationship to predefined colors.

1. Detection Boxes
These boxes show the selected colors detected on the camera image.

2. Add Button
This button adds color to the detection list.

3. Edit button
This button will open the Custom HSL Color window to edit/adjust the color you want to detect. The main items you will be adjusting are the color name field, the two color wheel wipers, the saturation min slider, and the luminance max slider. Here's how the Custom HSL Color window looks:



4. Enable Checkbox
This checkbox turns on/off the color you have added to the detection list.

5. Color Name
This is a text display of your chosen name in the Custom HSL Color window.



Main Window - Face Tracking



Face tracking will attempt to detect faces within the image. Face tracking uses calculations to detect eyes and a mouth. This does require additional processing and will slow the framerate. Also, detecting images within a video stream with many complicated objects will return false positives. Use Face Tracking against a white wall or non-complicated background. If you wish to detect specific faces, use the Object Tracking type, as you can train your face to be an object.

1. Detection Box
This box shows where a face has been detected on the camera image.

2. Face Tracking Checkbox
This checkbox will need to be enabled to track faces.

3. Camera Frame Rate
This displays the camera frame rate per second (fps) and the number of skipped frames.



Main Window - Custom Haar Tracking



Unless you have experience with computer vision, ignore this tracking type. In brief, this tracking type is used for computer vision specialists who generate HAAR Cascades in OpenCV-compatible v1 Haar XML files. Ensure the XML haar files are the v1 (first version) of the OpenCV Haar format or you will get an error when attempting to load a newer haar XML file. This is very CPU intensive and will most likely bring a slower computer to a halt. If the input cascade is not optimized, it will greatly affect framerate processing performance. Documenting this tracking type and generating HAAR v1 OpenCV-compatible XML files is out of the scope of this document.

1. Detection Box
This box shows where the camera image has detected a custom haar cascade.

2. Custom Haar Tracking Checkbox
This checkbox will need to be enabled to track custom haar cascades.

3. Camera Frame Rate
This displays the camera frame rate per second (fps) and the number of skipped frames.

Link to OpenCV v1 Haar Cascades: XML Files

Main Window - Object Tracking



This advanced computer vision learning tracking type allows you to teach the robot an object (such as a face, logo, etc.) and have it detect it. Computer vision learning is very experimental and requires patience and consistent lighting.

*Note: For best results with object training, consider that you are teaching the robot specific details of the object, not the object itself. This means the entire object must not be in the training square. Only details unique to that object need to be in the training square. For example, you may not wish to teach the robot a can of soda/cola by putting the entire can in the square. Merely put the logo in the square or any other identifying features.

1. Detection Box
This box shows a trained object detected on the camera image.

2. Train New Object Button
This button will open the Custom Object window to train new custom objects you want to detect. To train a new object, first enter the name of the object, then click in the camera image area to create a pink box; place your object in front of the camera in such a way that a unique detail of your object fills the box, click the learn selected area button, and then tilt your object slowly at different angles until the learning is complete. Here's how the Custom Object window looks:



3. Clear Memory Button
This button removes all the trained objects from the trained images window.

4. Learn While Tracking Checkbox
This checkbox enables the object learning module to keep learning the tracked object. Be aware that if this checkbox is left enabled, there is a chance that, over time, the module will start learning the objects around the tracked object.

5. Show Movement Tracer Checkbox
This checkbox enables the trajectory tracer to be displayed as the object moves.

6. Trained Images Display
This displays the objects trained in the train new object window.



Main Window - Motion Tracking



This observes changes within the camera image. The motion should not be confused with the "Movement" Setting from the configuration menu, as they are different and should not be used together. The Motion Tracking Type will detect a change in the camera image and return the changing area. For example, if your camera is stationary and you wave your hand in a small area of the camera image, you will see the motion display of your hand moving. If a robot moves during Motion Tracking Type, the entire image would have been changed, which is not helpful for tracking. So, the Motion Tracking Type is only beneficial for stationary cameras.

1. Detection Box
This box shows where motion has been detected on the camera image.

2. Motion Sensitivity Slider
This slider adjusts the amount of motion needed for the motion to be detected.

3. Minimum Object Size Slider
This slider allows you to select the size of the detected motion object before registering it as a detection.

4. Example Minimum Size Display
This display gives you a visual reference of how large (in pixel size) the detected object will have to be in the camera image display.

5. Check Every (frames) Drop-down
This dropdown allows you to select how many frames to wait between detection samples.



Main Window - Glyph Tracking



This tracking type will look for images of black and white squares. The camera robot skill will use a set of specific glyphs (1, 2, 3, and 4) for this tracking type. This tracking type will detect those glyphs if you download and print the glyph PDF in the link below. You may also visit the Camera configuration to set up augmented reality overlays on the glyphs. This means the camera will superimpose a selected image over the detected glyph. When tracking glyph images, the glyph will only execute its respective tracking script once until another glyph has been detected or the ClearGlyph control command has been called. To see all available controlcommand(), press the Cheat Sheet tab when editing scripts.

Glyph Downloads: Glyph PDF

1. Detection Box
This box shows where the glyph has been detected on the camera image.

2. Glyph Tracking Checkbox
This checkbox will need to be enabled to track glyphs.

3. Camera Frame Rate
This displays the camera frame rate per second (fps) and the number of skipped frames.



Main Window - YCbCr Tracking



This tracking type is much like multi-color. You can specify and fine-tune your color and add multiple colors. While multi-color uses classical RGB values, YCbCr uses blue-difference and red-difference chroma (Cb and Cr) and luma (Y) components.

1. Detection Box
This box shows where the glyph has been detected on the camera image.

2. Add Button
This button adds color to the detection list.

3. Edit Button
This button will open the Custom YCbCr Color window to edit/adjust the color you want to detect. The main items you will be adjusting are the color name field, the Cb sliders, the Cr sliders, and the Y sliders. Here's how the Custom YCbCr Color window looks:



4. Enable Checkbox
This checkbox turns on/off the color you have added to the detection list.

5. Color Name
This is a text display of your chosen name in the Custom YCbCr Color window.

Main Window - Grid



These grid lines are used for movement and servo tracking. With tracking enabled, a robot can move to keep the detected object in the center of the grid lines. Move the sliders to adjust the position of the grid lines on the camera image. The field of detection can be narrowed or expanded with the grid lines.

1. Grid Line Overlay
These grid lines are overlaid on the camera image and are always there, even if you make them completely transparent.

2. Grid Line Sliders
These sliders are for moving the grid lines. There are four sliders for each of the four grid lines.

3. Defaults Button
This button resets the grid lines back to their default position.

4. Grid Line Transparency Slider
This slider controls the transparency of the grid lines, from bold red to invisible.

Configuration - Servo/Movement Tracking



These settings set up how a robot reacts when an object is detected by one of the enabled tacking types. Servo, Movement, or Scripts are the three reaction types you can enable individually or simultaneously. The skill assumes the camera is mounted on the specified servos if servo tracking is checked. The servos will be moved from left to right, up to down, and down to track the detected object based on the servo settings that you have provided. The Movement reaction type is physically moving the entire robot toward an object. If Movement is checked, the robot will follow the detected object when visible using the project's movement panel. The movement panel may be an Auto Position, H-Bridge, or more. The robot will move forward, left or right, to follow the desired object. The Scripts tab of the camera device configuration menu is a Tracking Start and Tracking End script. When an object is detected, the Tracking Start script will execute. The Tracking End script will run when the camera no longer tracks an object.

1. Servo Tracking Checkbox
This checkbox will enable X and Y-axis Servos to move to track a detected object.

2. Relative Position/Grid Line Checkboxes
These checkboxes allow the servos to track the detected object via relative position (moving to the center of the camera image) or using the grid lines (moving to wherever the center of the grid lines is set). Using relative position assumes a stationary camera is being used, and using grid lines assumes a pan/tilt mechanism is being used.

3. Servo Setup Drop-downs
These dropdowns allow for the setup of the X and Y axis Servos. You can set board index, port number, min and max position limits, and multiple servos. You can also invert the servo direction with the included checkbox.

4. Horizontal/Vertical Increment Steps Drop-downs
These dropdowns adjust the number of steps the servos will move toward the detected object. The smaller the number, the more precise the movements will be.

Configuration - Scripts



This section of the Scripts tab includes a checkbox to enable the execution of tracking scripts. You can add tracking start and end scripts and use dropdowns to select how many frames to delay before the tracking start/end scripts execute and sort by the detected object (blob) order.

This section includes all the variables that are used with the camera skill. You can change the variable names here if you'd like. You can use these variables throughout your scripts and applications. You can view their value or state in real-time with the Variable Watch skill. There is also a dropdown for selecting the maximum number of objects to detect. Each detected object will add an underscore and number to the end of the variables to distinguish one from another.

$CameraIsTracking
This variable returns true or false if the camera tracks an object.

$CameraObjectCenterX
The X-pixel location of the current detected object. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectCenterY
The Y-pixel location of the current detected object. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectColor
The current detected object's color if the color tracking type is selected. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectRotation
The rotation in degrees of the object. Not all tracking types support this value. Multicolor and Glyph tracking types do support the rotation, but not others.
$CameraObjectCount
How many detected objects? This is how many there are for every variable with a _x appended.

$CameraObjectGlyphNumber
The current detected glyph number from the glyph PDF.

$CameraObjectHeight
The current object detected height. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectHorizontalQuadrant
The horizontal quadrant that the detected object is in. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectName
If the current tracking type is Object, this is the object's name. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectVerticalQuadrant
The vertical quadrant that the detected object is in. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraObjectWidth
The width in pixels of the detected object. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$CameraQRCode
If QR code tracking type is selected, this is the text that is read from the detected QR code.

$CameraResolutionHeight
The current height resolution of the camera. You may need this if using another robot skill to scale how many height pixels there are in the camera.

$CameraResolutionWidth
The current width resolution of the camera. You may need this if using another robot skill to scale how many width pixels there are in a camera frame.

$CameraTrackingType
The current detected object tracking type. Based on your settings, there may be more of these each appended with a _x , where x is the number.

$IsCameraActive
Sets a true or false if the camera is currently active (running).





This section executes scripts when the corresponding glyph is detected. Find more information about glyphs in the Glyph Tracking section.



In this section, you can generate a list of different QR Code texts and enter a script to execute when that certain text is detected. You can also generate a script that executes when a QR Code not on your list is detected. There are also buttons included to manage your list of QR Codes.

Configuration - Augmented Reality



1. Select Image Buttons
These buttons assign an image to be displayed when the corresponding glyph is detected. Find more information about glyphs in the Glyph Tracking section.

Configuration - Detection



1. Load Button
This button loads custom haar cascades (in Open CV Haar v1 XML format). You can download custom cascades from OpenCV on github.

2. Minimum Size Drop-down
This dropdown sets up the minimum size the detected face (in pixels) must be to register as a detection.

3. Maximum Size Drop-down
This dropdown sets up the maximum size the detected face (in pixels) will have to be to register as a detection.

4. Minimum Detection Count Drop-down
This dropdown sets the minimum of detected frames the face must present to register as a detection. There's more information on Face Tracking above.

Configuration - Media



1. Change Button
This button lets you change the save location on your PC where your robot took photos with the camera device.

2. Snapshot Quality Drop-down
This dropdown sets up the percentage of JPEG quality you would like (10 to 100%). The larger the percentage, the larger the file size will be.

3. Video Capture Codec Drop-down
This dropdown sets up the video capture compression format (WMV1, WMV2, or H263P5)

4. Bit Rate Field
This value determines the codec resolution and size of each video frame.

5. Insert Video Title Checkbox
This checkbox enables the Video Title text to be shown at the beginning of your recorded video.

6. Title Length Drop-down
This dropdown allows you to set how long the title will be displayed (in seconds) at the beginning of your recorded video.

7. Title Text Field
This field allows you to enter the text title you want displayed at the beginning of your recorded video. The title can also be a script variable if you'd like.

Configuration - Advanced



1. Title Field
This field allows you to change the text title of the camera device skill. *Note: Changing the title here will also change the title in the controlCommand() associated with this skill.

2. Camera Image Orientation Drop-down
This dropdown sets the orientation of the camera image. If your camera is mounted in an odd orientation, you can use this dropdown to correct how it displays the camera image on the screen. There are 16 different orientation options.

3. Stop Camera on Error Checkbox
This checkbox is for plug-in troubleshooting. It allows the camera device to stop if an error occurs and allows you to show the error to Synthiam in the debug window.

4. Frame Rate Initialization Field
This field allows you to adjust the frame rate when the camera initializes. It's best to leave this value at -1.

How to Use Camera Device

1) Add the Camera Device skill to your ARC project (Project -> Add Skill -> Camera -> Camera Device).

2) Select the Camera you would like to use from the Video Device dropdown.

3) Select the resolution. If the camera image doesn't show up, you may have selected an unsupported resolution for that camera.

4) Press the Start/Stop Button to begin transmitting camera images.

5) Select a tracking type in the tracking tab to track objects using the camera image data.

6) Select the other settings tabs or the triple dots to configure the tracking type (if applicable).


Video Resolutions and Performance

Machine vision and computer recognition are very high CPU-intensive processes. The cameras for computer vision are much less resolution than what you, as a human, would use for recording a birthday party. If you were to run computer vision to recognize objects and decode frames at HD quality, your computer response would grind to a halt.

160x120 = 57,600 Bytes per frame = 1,152,000 Bytes per second
320x240 = 230,400 Bytes per frame = 4,608,000 Bytes per second
640x480 = 921,600 Bytes per frame = 18,432,000 Bytes per second

So, at 320x240, your CPU processes a complex algorithm on 4,608,000 Bytes per second. When you move to a mere 640x480, it's 18,432,000 Bytes per second.

To expand on that, 4,608,000 Bytes per second is just the data, not including the number of CPU instructions per step of the algorithm(s). Do not let television shows, such as Person Of Interest, make you believe that computer vision and CPU processing are accessible in real-time; many of us are working on it! We can put 4,608,000 Bytes into perspective by relating that to a 2-minute MP3 file. Imagine your computer processing a 2-minute MP3 file in less than 1 second - that is what vision processing for recognition is doing at 320x240 resolution. As soon as you increase the resolution, the CPU has to process an exponentially larger amount of data. Computer vision recognition does not require as much resolution as your human eyes, as it looks for patterns, colors, or shapes.

If you want to record a birthday party, do not use a robot camera - buy a real camera. Synthiam software algorithms are designed for vision recognition with robotics.


Use Camera with Code

You may also instruct the Camera Device Skill to change settings programmatically through code. The ControlCommand() can be called in EZ-Script to change the Camera Device settings. Learn more about the ControlCommand() here.


Troubleshooting

If you experience camera troubles with disconnections over WiFi or USB, it should be addressed before attempting a workaround via reconnection scripts. It's to identify the root cause of the camera disconnection to ensure a stable and reliable robot operation. Addressing the underlying issue will provide a more permanent solution than a script that repeatedly attempts to reconnect the camera.

Power issues, servo stalling, Wi-Fi saturation, saturated USB bandwidth, and open network WiFi vulnerabilities can all contribute to camera disconnections. Investigating these potential causes and taking appropriate measures to resolve them will help maintain a consistent connection to the camera.

A USB camera or TCP wifi camera connection will be maintained for years if it is not disconnected. The cause of the disconnection should be identified, as a reconnect script is a bandaid to a much larger problem.

  • Power. The power consumption of your robot may be exceeding the power supply. When this happens, the EZB and camera may brown out. This will disconnect the camera.
  • Servos Stalling. The servos are stalling, which means they are attempting to move further than their limits or lifting something too heavy. If this is the case, it's essentially shorting out the power supply, which will cause a brownout
  • Wifi saturation. Depending on your environment, you may be experiencing wifi saturation. This is when too many wifi devices are within a localized area, causing interference. You can use a wifi scan tool to find a free wifi channel. We have a tool and info available on this page: https://synthiam.com/Support/troubleshooting/Troubleshoot-WiFi-Connections (scroll down to find WiFi Channel/Signal Scan)
  • WiFi Open Network. If your WiFi EZB is in access point mode, it may allow connections from anyone with a wifi device. That means a phone, laptop, TV, dishwasher, etc.. Without a passphrase or password on the wifi network, anyone can connect to it. Having more connections can cause WiFi-enabled EZBs to drop other connections.
  • USB Saturation. Computers may have multiple USB ports, but they all may be connected internally to a hub. The bandwidth will be limited if too many devices are on the same port. Check with your PC manufacturer or the device manager to find a USB port that has the least number of devices connected.

Related Tutorials

Related Hack Events

Related Robots

Related Questions


ARC Pro

Upgrade to ARC Pro

ARC Pro will give you immediate updates and new features needed to unleash your robot's potential!

PRO
Australia
#1   — Edited

It appears that the GLYPH pdf are no longer available.  I followed the links and got

Quote:

This synthiam.com page can’t be found

Can I get the sample pdf please?

PRO
Synthiam
#2   — Edited

Link fixed

Austria
#3  

Is there also a jpeg file for the glyphs.

#4  

Hey Guys. Dusted off an old iotiny tank project with my son. Getting this error with the camera. Using 7.4V for a IOTiny source. Anyone seen this?

Camera Initialized: EZB://10.0.1.231:24 @ 320x240 EZ-B v4 Camera Error: System.Exception: Client disconnected at EZ_B.EZBv4Video.aenVYfUEGW(EZTaskScheduler , Int32 , Object ) Camera Disabled

Thanks!

#5  

Hello,

Color tracking works. Motion tracking works. Face tracking doesn't work. Version 2020.09.08.00.

  1. I selected my device/camera.
  2. I set the resolution to 640x408
  3. I clicked the green Start button.
  4. Camera went on.
  5. My face was there.
  6. I selected the Tracking tab
  7. I selected "Face".

Expected: bounding boxes around my face Actual: No bounding boxes.

Is this a SOFTWARE DEFECT? Or user error?

I also tried Color and Motion. Both of those worked just fine.

Thomas Messerschmidt

PRO
Synthiam
#6  

Face tracking works. Perhaps check the settings of the face tracking in the camera config. Also ensure correct lighting. Based on your camera resolution, you may need to tweak the settings. Use the question marks for assistance on what different settings do

also note that this thread is the camera device manual. And in this manual page are the instructions for the face tracking settings:)

#7   — Edited

DJ,

[u] I found the issue: [/u]

  1. The "face detection options"/ "Max Size" adjustment needs to be set at least as large as the height of the video resolution. For example, for a resolution of 650X360, the Max Size needs to be set at 360 or more. At 640X480, Max Size needs to be set at 480 or more. if I set the Max Size less than the height of the video's height, face tracking no longer works. Also, a resolution of 1280x720 doesn't work at all because Max Size has a preset maximum of 500.

  2. Also, It might be the fault of my camera, but I cannot "Start" the camera with resolutions of less than 650X360.

  3. Also,  ARC crashes and shuts down when I change the camera resolution more than 6 or 8 times.

Thanks for getting back to me so quickly.

Thomas

#8  

So I have always used EZ camera on projects but now I want to use another USB camera for another robot,to be clear I can do all the same stuff with a better USB camera if using on Latte Panda USB port right? Object,color tracking?

PRO
Synthiam
#9  

Yes - you can use a USB camera

#10  

Ok thanks great to know will try it out now!

#11   — Edited

I guess this is as good a place to say this since we don't have a general discussion area of the forum and this not a question or robot comment, but I have to say I am very impressed with the improvements to documentation lately.  @Djsures did you hire someone to help with documentation or just determine that enough of us were complaining that videos as the primary documentation were difficult for long term reference? :)

The documentation of this skill in particular is absolutely fantastic, but I have also noticed it in others.  Videos are great for demonstration of capabilities, but when you want to learn how to set up and configure something, nothing beats a good user manual you can print out and mark up as needed....

Alan

PRO
Synthiam
#12  

That's great to hear - jeremie will appreciate the feedback. It's what he's been working on:)

PRO
USA
#14  

Thank you Alan for pointing that out.

User-inserted image

(*) RTFM = Read the Friendly Manual

Portugal
#15  

Good work jeremie. Had noticed that lately documentation is fast and spot on.cool

PRO
Synthiam
#16  

He’s got me on the kick to make sure I keep updating me content as well.:)

PRO
Canada
#18  

Thank you, everyone! I definitely have put a lot of work into it, I've been taking a break from it for a little bit here but I'll be back at it over the Holiday break. It definitely encourages me to hear that you appreciate the effort!

#19  

It's almost like Facebook here lately with all the "Like" going on, but that's a good thing! Even with FB falling apart in the courts lately.xD

PRO
Australia
#20  

I have run into problems with Face Tracking on my Pepper robot. If I use the USB camera you recommended, Face Tracking does not work unless the resolution is set to 320x240. However, this camera does not display video properly at this setting - it has to be 640x480 or higher to get a meaningful image. If I use the Surface Go2 front camera instead, again I can't get Face Tracking to work either because I can't set this camera's resolution to 320x240. Any ideas would be appreciated.

#21  

When the resolution has been changed, the settings for optimizing face tracking performance must be adjusted.  See this manual above for information on the Detection setting in the device settings.

*Note: We moved your question to this thread because it was asked in an unrelated conversation.

User-inserted image

PRO
Australia
#22  

OK. Very useful advice. I adjusted detection settings to 500 max and Face Tracking worked. It was set to 300 by default. A simple fix when you know what to do.

PRO
Synthiam
#23  

Sure is! I always thought that should be automatically adjusted when the resolution was changed. But if someone manually fine tunes the value, we don’t want to override and change it.

oh, there’s also a setting that will take the high res video resolution and lower it for processing. It’s under the Advanced tab. So if you don’t need the high res to save some cpu, that option is useful.

#24   — Edited

Hello DJ I want to setup face tracking but my neck system has one servo to rotate the head and two servos up and down movement independent of each other as seen in the picture below.

In the skill you support a two servo solution I am hope you can tell me a way I can get this work.

Is my only option to use a Y connector and make a hardware mod to reverse one of the servos?

User-inserted image

#26  

Thank you DJ!  I figured there was a way to do this but I did not register this when I seen it.