Neural Network Learning Proccess to Be Shown As Evolution

Evolution simulator clearly shows how neural network learns on the example of simplest virtual creatures evolution
10 September 2018   165

Keiwan Donyagard published Evolution simulator, in which the user creates a creature from bones, muscles and joints in the form of lines and dots, and the creature develops using a neural network as the brain. This is reported by The Next Web.

The creature evolves, performing the simplest actions: running, jumping and climbing up. The process clearly demonstrates the stage-by-stage learning of the neural network: it learns to analyze the distance to the ground and the number of points of contact, the direction of movement of the individual and speed, location in space and other parameters.

AI takes into account the position of the object in space, the direction of motion and speed, the distance to the ground, as well as the number of points of contact with it. During attempts, copies of the creature appear, from which the neural network chooses the two most successful ones, based on the conditions of the problem. Parameters are used to create new creatures and the loop is repeated until the task is executed correctly.

AI to be Used to Create 3D Motion Sculptures

The system developed by the MIT and Berkeley scientists is called MoSculp and is based on artificial inteligence
21 September 2018   110

MoSculp, the joint work of MIT scientists and the University of California at Berkeley, is built on the basis of a neural network. The development analyzes the video recording of a moving person and generates what the creators called "interactive visualization of form and time." According to the lead specialist of the project Xiuming Zhang, software will be useful for athletes for detailed analysis of movements.

At the first stage, the system scans the video frame-by-frame and determines the position of key points of the object's body, such as elbows, knees, ankles. For this, scientists decided to resort to the OpenPose library, developed by the Carnegie Mellon University. Based on the received data, the neural network compiles a 3D model of the person in each frame, and calculates the trajectory of the motion, obtaining a "motion sculpture".

At this stage, the image, according to the developers, suffers from a lack of textures and details, so the application integrates the "sculpture" in the original video. To avoid overlapping, MoSculp calculates a depth map for the original object and the 3D model.

MoSculp 3D Model
MoSculp 3D Model

The operator can adjust the image during the processing, select the "sculpture" material, color, lighting, and also what parts of the body will be tracked. The system is able to print the result using a 3D printer.

The team of researchers announced plans to further develop the MoSculp technology. Developers want to achieve from the processing system more than one object on the video, which is currently impossible. The creators of the technology believe that the program will be used to study group dynamics, social disorders and interpersonal interactions.

The principle of creating a 3D model based on human movements has been used before. For example, in August 2018, scientists at the same University of California at Berkeley demonstrated an algorithm that transfers the movements of one person to another.