scholarly journals Real-Time Visual Tracking System Suggested by Saccade and Pursuit Eye movements.

1997 ◽  
Vol 15 (3) ◽  
pp. 474-480
Author(s):  
Yoshinori Takeuchi ◽  
Zeng-Fu Wang ◽  
Noboru Ohnishi ◽  
Noboru Sugie
Keyword(s):  
Eye Movements ◽  
Real Time ◽  
Visual Tracking ◽  
Tracking System ◽  
Pursuit Eye Movements

A Control Systems Model of Smooth Pursuit Eye Movements with Realistic Emergent Properties

1989 ◽  
Vol 1 (1) ◽  
pp. 116-122 ◽  
Author(s):  
R. J. Krauzlis ◽  
S. G. Lisberger
Keyword(s):  
Eye Movements ◽  
Visual Tracking ◽  
Smooth Pursuit ◽  
Oculomotor System ◽  
Difficult Problem ◽  
Visual Signals ◽  
Emergent Properties ◽  
Smooth Pursuit Eye Movements ◽  
Pursuit Eye Movements ◽  
Systems Model

Visual tracking of objects in a noisy environment is a difficult problem that has been solved by the primate oculomotor system, but remains unsolved in robotics. In primates, smooth pursuit eye movements match eye motion to target motion to keep the eye pointed at smoothly moving targets. We have used computer models as a tool to investigate possible computational strategies underlying this behavior. Here, we present a model based upon behavioral data from monkeys. The model emphasizes the variety of visual signals available for pursuit and, in particular, includes a sensitivity to the acceleration of retinal images. The model was designed to replicate the initial eye velocity response observed during pursuit of different target motions. The strength of the model is that it also exhibits a number of emergent properties that are seen in the behavior of both humans and monkeys. This suggests that the elements in the model capture important aspects of the mechanism of visual tracking by the primate smooth pursuit system.

scholarly journals Real-time visual tracking system modelling in MPSoC using platform based design

2009 ◽  
Author(s):  
Zai Jian Jia ◽  
Tomás Bautista ◽  
Antonio Núñez ◽  
Cayetano Guerra ◽  
Mario Hernández
Keyword(s):  
Real Time ◽  
Visual Tracking ◽  
Tracking System ◽  
System Modelling ◽  
Platform Based Design

scholarly journals Study on the Moving Target Tracking Based on Vision DSP

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6494
Author(s):  
Xuan Gong ◽  
Zichun Le ◽  
Hui Wang ◽  
Yukun Wu
Keyword(s):  
Real Time ◽  
Visual Tracking ◽  
Tracking System ◽  
Direct Memory Access ◽  
Optimization Techniques ◽  
Tracking Algorithm ◽  
Scale Transformation ◽  
Time Performance ◽  
System Resources ◽  
The Impact

The embedded visual tracking system has higher requirements for real-time performance and system resources, and this is a challenge for visual tracking systems with available hardware resources. The major focus of this study is evaluating the results of hardware optimization methods. These optimization techniques provide efficient utilization based on limited hardware resources. This paper also uses a pragmatic approach to investigate the real-time performance effect by implementing and optimizing a kernel correlation filter (KCF) tracking algorithm based on a vision digital signal processor (vision DSP). We examine and analyze the impact factors of the tracking system, which include DP (data parallelism), IP (instruction parallelism), and the characteristics of parallel processing of the DSP core and iDMA (integrated direct memory access). Moreover, we utilize a time-sharing strategy to increase the system runtime speed. These research results are also applicable to other machine vision algorithms. In addition, we introduced a scale filter to overcome the disadvantages of KCF for scale transformation. The experimental results demonstrate that the use of system resources and real-time tracking speed also satisfies the expected requirements, and the tracking algorithm with a scale filter can realize almost the same accuracy as the DSST (discriminative scale space tracking) algorithm under a vision DSP environment.

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