DeepAI AI Chat
Log In Sign Up

Automatic Recognition of Mammal Genera on Camera-Trap Images using Multi-Layer Robust Principal Component Analysis and Mixture Neural Networks

The segmentation and classification of animals from camera-trap images is due to the conditions under which the images are taken, a difficult task. This work presents a method for classifying and segmenting mammal genera from camera-trap images. Our method uses Multi-Layer Robust Principal Component Analysis (RPCA) for segmenting, Convolutional Neural Networks (CNNs) for extracting features, Least Absolute Shrinkage and Selection Operator (LASSO) for selecting features, and Artificial Neural Networks (ANNs) or Support Vector Machines (SVM) for classifying mammal genera present in the Colombian forest. We evaluated our method with the camera-trap images from the Alexander von Humboldt Biological Resources Research Institute. We obtained an accuracy of 92.65 mammal genera and a False Positive (FP) class, using automatic-segmented images. On the other hand, we reached 90.32 genera, using ground-truth images only. Unlike almost all previous works, we confront the animal segmentation and genera classification in the camera-trap recognition. This method shows a new approach toward a fully-automatic detection of animals from camera-trap images.

READ FULL TEXT

page 1

page 3

page 4

page 9

01/27/2017

Camera-Trap Images Segmentation using Multi-Layer Robust Principal Component Analysis

Camera trapping is a technique to study wildlife using automatic trigger...
10/25/2011

Face Recognition Based on SVM and 2DPCA

The paper will present a novel approach for solving face recognition pro...
06/22/2017

Fractal dimension analysis for automatic morphological galaxy classification

In this report we present experimental results using Haussdorf-Besicovic...
03/10/2021

Principal component-based image segmentation: a new approach to outline in vitro cell colonies

The in vitro clonogenic assay is a technique to study the ability of a c...
07/25/2021

Denoising and Segmentation of Epigraphical Scripts

This paper is a presentation of a new method for denoising images using ...