Using Feed-Forward Neural Networks for Data Association on Multi-Object Tracking Tasks
نویسندگان
چکیده
This article presents an approach for data association in single camera, multi-object tracking scenarios using feed-forward neural networks (FFNN). The challenges of data association are object occlusions and changing features which are used to describe objects during the process. The presented algorithm within this article can be applied to any kind of object which has to be tracked, e.g. persons and vehicles. This approach arises within a project to detect critical behavior of persons. Besides, person tracking is one of the most challenging scenarios. People have different velocities and often change the moving direction. In addition, a variety of occlusions are caused by the movement as a group. Also in most surveillance scenarios the illumination conditions are not optimal. The usage of a feed-forward neural network is a mostly new approach in this research field. The advantage is the lightweight computational complexity and the fixed termination time in contrast to recursive neural networks like Hopfield networks which are used for plot association during radar tracking. FFNN is a non-probabilistic approach in contrast to common algorithms within this filed. They deliver decisions not probability values. The handling of the FFNN output will be presented in this article. During the evaluation we will show that the developed approach is capable to handle completely different scenarios like tracking people moving mostly straight forward but also complex scenarios like a soccer game.
منابع مشابه
An Unsupervised Learning Method for an Attacker Agent in Robot Soccer Competitions Based on the Kohonen Neural Network
RoboCup competition as a great test-bed, has turned to a worldwide popular domains in recent years. The main object of such competitions is to deal with complex behavior of systems whichconsist of multiple autonomous agents. The rich experience of human soccer player can be used as a valuable reference for a robot soccer player. However, because of the differences between real and simulated soc...
متن کاملPREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS
Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, artificial neural networks (ANN) for predicting compressive strength of cubes and durability of concrete containing metakaolin with fly ash and silica fume with fly ash are developed at the age of 3, 7, 28, 56 and 90 days. For building these...
متن کاملPrediction of Permanent Earthquake-Induced Deformation in Earth Dams and Embankments Using Artificial Neural Networks
This research intends to develop a method based on the Artificial Neural Network (ANN) to predict permanent earthquake-induced deformation of the earth dams and embankments. For this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. In order to predict earthquake-induced deformation o...
متن کاملConvolutional Gating Network for Object Tracking
Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem. The paper presents a new model for combining convolutiona...
متن کاملApplication of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data
This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. F...
متن کامل