Human identity recognition is an important yet underaddressed
problem. Previous methods were strictly limited
to high quality photographs, where the principal techniques
heavily...
Local part-based human detectors are capable of handling partial occlusions efficiently and modeling shape articulations flexibly, while global shape template-based human detector...
Zhe Lin, Larry S. Davis, David S. Doermann, Daniel...
In recent years, local pattern based object detection and recognition have attracted increasing interest in computer vision research community. However, to our best knowledge no p...
Yadong Mu, Shuicheng Yan, Yi Liu, Thomas S. Huang,...
We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient ba...
Significant research has been devoted to detecting people
in images and videos. In this paper we describe a human detection
method that augments widely used edge-based features
...
William Robson Schwartz, Aniruddha Kembhavi, David...
Dr. Fatih Porikli is a senior principal research scientist and project manager at Mitsubishi Electric Research Labs (MERL), Cambridge, USA. He received his PhD specializing in vide...
In this paper, a novel feature named Adaptive Contour
Feature (ACF) is proposed for human detection and segmentation.
This feature consists of a chain of a number of
granules in...
Wei Gao (Tsinghua University), Haizhou Ai (Tsinghu...
This paper proposes a novel descriptor, granularitytunable
gradients partition (GGP), for human detection.
The concept granularity is used to define the spatial and angular
unce...
Yazhou Liu (Harbin Institute of Technology), Shigu...