Rhonda Software

Highest quality full cycle software development.

Expert in areas of Computer Vision, Multimedia, Messaging, Networking and others. Focused on embedded software development. Competent in building cross-platform solutions and distributed SW systems.

Offer standalone custom solutions as well as integration of existing products. Opened for outsourcing services.

Visit us at: http://www.rhondasoftware.com

Face recognition

Posted on : 01-06-2022 | By : rhondasw | In : Demo, Demo video, Demo videos, Face recognition, YouTube

0

The face recognition demo shows person facial feature training via a single photo and subsequent face matching on the live video stream, using VisionLabs’ library integrated onto the H22 System on a Module (SoM).

Pose Estimation and Activity recognition demo

Posted on : 22-04-2022 | By : rhondasw | In : Demo, Demo video, Demo videos, OpenCV, YouTube

0

This demo showcases real-time Human Pose Estimation, based on the Open Pose library, ported onto the camera platform, and designed by Rhonda’s Activity Recognition neural network for human behavior recognition. The two Deep Learning Neural Networks (DNN), along with the video pipeline, run on the Rhonda Software CV22 System on a Module (CV22 SoM).

People counting with top-mounted camera

Posted on : 03-03-2010 | By : rhondasw | In : Demo, Demo video, Demo videos, YouTube

17

people_counter.avi

Marketing researches are area where required to analyze a lot of data. E.g. we want to understand how many people are visiting a bank. In order to count this value, we need to count each man or woman which are entering to or exiting from the bank. For resolving this task there are a lot of approaches: e.g. use special gate with laser or mechanical counter. Though there are people counting tasks where such approaches cannot work or too unuseful. E.g. barrier cannot be used where people flow is very high, and laser counters have limitations as well.

Opposite the approaches above, we found papers where top-mounted camera is used for resolving the people counting task.

Object recognition (“instruments recognition”)

Posted on : 01-02-2010 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, YouTube

15

tools.avi

This object recognition algorithm is based on own pattern-matching algorithm. The algorithm is able to recognize pre-trained objects which are defined with special set of templates.

USD banknotes recognition

Posted on : 15-12-2009 | By : Yuri Vashchenko | In : Demo, Demo video, Demo videos, OpenCV, YouTube

11

The currency recognition demo application works under Windows XP, Intel P4 3GHz. Quality of recognition: 85%. The solution is cross-platform. The application was tested on Linux, ARM11 and on Linux/Windows, Intel Atom.

Barcode recognition (mobile platform)

Posted on : 25-11-2009 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, YouTube

3

Interesting details can be found at: http://www.computer-vision-software.com/blog/2009/10/barcode

Object Recognition (Nike logo)

Posted on : 22-10-2009 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, OpenCV, YouTube

11

nike.avi

This is a demo video of the invariant orientation and scale fast object detection algorithm. The algorithm is a robust in cases when the object is deformed a little 🙂

Audience Measurement (face tracker, gender recognition, attention recognition, etc)

Posted on : 05-10-2009 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, OpenCV, YouTube

13

am-3.avi

This is a demo video of Rhonda Audience Measurement system (MyAudience product, www.MyAudience.com).

Barcode recognition

Posted on : 29-07-2009 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, YouTube

1

barcodes-2.avi

Description

Here you can find a demo of the barcode detection and recognition routine. The current version is set up to detect a barcode labels mostly oriented horizontally and vertically. The routine processes each frame of the video stream and scans it trying to detect a barcode starting position, relying on the appearance specific of the barcode labels. As long as a potential starting position detected the routine applies the set of the image filters to increase the readability of the scanned window. Then recognition algorithm tries both to read and validate the barcode label starting from the detected point. You may see for yourself that such combination of detection and recognition algorithms works pretty well.
This demo works with UPC-A and EAN-13 barcode types.

Gender detection

Posted on : 22-07-2009 | By : Aleksey Kodubets | In : Demo, Demo video, Demo videos, YouTube

34

Description

In this post we present a video demo of the gender classifier. This classifier is adapted for frontal- and near to frontal-oriented faces. It is capable to provide the real-time gender recognition with the invariance to complicated lighting conditions. The foundation of the implemented method is an AdaBoost powered extraction of the gender-descriptive features along with the further separation of male / female subsets for learning of the decision-making routine.
The classifier works in the conjunction with face-detector and tries to classify all found faces on the each frame. The achieved accuracy of correct classification is 90-92%, though on small faces (less then 32×32 pixels) returned by face-detector the accuracy of gender recognition could reduce to 80-88%.