Robust Object Tracking Based on Self-adaptive Search Area

11/21/2017
by   Taihang Dong, et al.
0

Discriminative correlation filter (DCF) based trackers have recently achieved excellent performance with great computational efficiency. However, DCF based trackers suffer boundary effects, which result in the unstable performance in challenging situations exhibiting fast motion. In this paper, we propose a novel method to mitigate this side-effect in DCF based trackers. We change the search area according to the prediction of target motion. When the object moves fast, broad search area could alleviate boundary effects and reserve the probability of locating the object. When the object moves slowly, narrow search area could prevent the effect of useless background information and improve computational efficiency to attain real-time performance. This strategy can impressively soothe boundary effects in situations exhibiting fast motion and motion blur, and it can be used in almost all DCF based trackers. The experiments on OTB benchmark show that the proposed framework improves the performance compared with the baseline trackers.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/21/2019

Effects of Blur and Deblurring to Visual Object Tracking

Intuitively, motion blur may hurt the performance of visual object track...
research
12/04/2015

Staple: Complementary Learners for Real-Time Tracking

Correlation Filter-based trackers have recently achieved excellent perfo...
research
06/04/2019

Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking

Visual object tracking is one of the major challenges in the field of co...
research
07/10/2022

SRRT: Search Region Regulation Tracking

Dominant trackers generate a fixed-size rectangular region based on the ...
research
04/29/2021

LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search

Object tracking has achieved significant progress over the past few year...
research
06/17/2018

High Speed Kernelized Correlation Filters without Boundary Effect

Recently, correlation filter based trackers (CF trackers) have attracted...
research
06/11/2020

Deep Convolutional Likelihood Particle Filter for Visual Tracking

We propose a novel particle filter for convolutional-correlation visual ...

Please sign up or login with your details

Forgot password? Click here to reset