Mobile Face Tracking: A Survey and Benchmark

05/24/2018
by   Yiming Lin, et al.
0

With the rapid development of smartphones, facial analysis has been playing an increasingly important role in a multitude of mobile applications. In most scenarios, face tracking serves as a crucial first step because more often than not, a mobile application would only need to focus on analysing a specific face in a complex setting. Albeit inheriting many commons traits of the generic visual tracking problem, face tracking in mobile scenarios is characterised by a unique set of challenges. In this work, we propose iBUG MobiFace benchmark, the first mobile face tracking benchmark consisting of 50 sequences captured by smartphone users in unconstrained environments. The sequences contain a total of 50,736 frames with 46 distinct identities to be tracked. The tracking target in each sequence is selected with varying difficulties in mobile scenarios. In addition to frame by frame bounding box, the annotations of 9 sequence attributes(e.g. multiple faces) are provided. We further provide a survey of 23 state-of-the-art visual trackers and a comprehensive quantitative evaluation of these methods on the proposed benchmark. In particular, trackers from two most popular frameworks, namely, correlation filter-based tracking and deep learning-based tracking, are studied. Our experiment shows that (a) the performance of all existing generic object trackers drops significantly on the mobile face tracking scenario, suggesting the need of more research effort into mobile face tracking, and (b) the effective combination of deep learning tracking and face-related algorithms(e.g. face detection) provides the most promising basis for future developments in the field. The database, annotations and evaluation protocol/code will be made publicly available on the iBUG website.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 2

08/03/2020

LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark

In this paper, we present a Large-Scale and high-diversity general Therm...
09/13/2017

Densely tracking sequences of 3D face scans

3D face dense tracking aims to find dense inter-frame correspondences in...
03/17/2017

Need for Speed: A Benchmark for Higher Frame Rate Object Tracking

In this paper, we propose the first higher frame rate video dataset (cal...
03/27/2018

Event-based Dynamic Face Detection and Tracking Based on Activity

We present the first purely event-based approach for face detection usin...
05/12/2017

TraX: The visual Tracking eXchange Protocol and Library

In this paper we address the problem of developing on-line visual tracki...
08/21/2020

Line-Circle-Square (LCS): A Multilayered Geometric Filter for Edge-Based Detection

This paper presents a state-of-the-art filter that reduces the complexit...
06/07/2017

DeepSketch2Face: A Deep Learning Based Sketching System for 3D Face and Caricature Modeling

Face modeling has been paid much attention in the field of visual comput...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.