Computer Vision Detection icon

2.9 by EmptyBrain


Sep 7, 2017

About Computer Vision Detection

The application will allow you to experiment with computer vision algorithms.

The application includes such algorithms:

- Camshift

- Corner Detector

- Viola-Jones Method

- Color Detector

- Canny Detector

- Gray

- HSV

- Morphological Transformations

- Motion Detector

- Shape Detector

- FAST feature detector

- Facial Landmark

To use these algorithms, click the menu button in the action bar.

You can choose these screen resolutions: 480x320, 640x480,720x480,1280x720,1920x1080.

And these default haar cascades: Frontal Face(Lite), Full Body, Eye, Frontal Cat Face, Frontal Face(complicated), or load your own cascade.

These algorithms are able:

1. Camshift - Just click on the object and it will be tracked

2. Viola-Jones method - To use this algorithm you need to select the desired haar cascade in the settings and enable this algorithm.

3. Color Detector - All colors falling in the range of colors you choose will be circled.

4. Corner Detector - The algorithm looks for angles (singular points).

5. Gray - This effect translates the image into a halftone mode.

6. HSV - This effect translates the image into an HSV color gamut.

7. Canny Detector - This effect determines the boundaries of the image

8. FAST - this algorithm detect features on image

9. Morphological Transformations - transforms images by combining two basic functions: erode and dilate

10. Shape detector - defines basic geometric shapes (Triangle, Rectangle, Pentagon, Hexagon, Circle, N-gon)

11. Motion detector - track motion on video stream

12. Facial landmark - detects the person, their landmarks and shows if the person is smiling.

*Application have the advertising, which can be disabled in the settings.*

What's New in the Latest Version 2.9

Last updated on Sep 7, 2017

- Fixed Bugs

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Additional APP Information

Latest Version

Request Computer Vision Detection Update 2.9

Uploaded by

Akash Jatav Jatav

Requires Android

Android 4.0.3+

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Computer Vision Detection Screenshots

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