Action Recognition in Still Images using Residual Neural Network Features
نویسندگان
چکیده
منابع مشابه
Neural network based steganalysis in still images
Seganalysis has recently attracted researchers’ interests with the development of information hiding techniques. In this paper we propose a new method based neural network to get statistics features of images to identify the underlying hidden data. We first extract features of image embedded information, then input them into neural network to get output. And experiment results indicate this met...
متن کاملJapanese Manual Alphabet Recognition from Still Images Using a Neural Network Model
Japanese manual alphabet is used mainly by hearing impaired persons as complements of sign language. Using neural network model, a Japanese manual alphabet recognition system is implemented. Still images of finger shapes from 2 directions are used as inputs of a multi-layer perceptron and the classification of the alphabet is the output. Overall performance of recognition is around 88% in avera...
متن کاملEncoding Accelerometer Signals as Images for Activity Recognition Using Residual Neural Network
Human activity recognition using a single 3-axis accelerometer plays an important and fundamental role in daily monitoring using wearable sensors and devices. In this paper, we address the recognition problem by encoding 3channel accelerometer signals as images and using transferring learning approach. Though projecting time series onto image space is not a new topic, our method is the first ti...
متن کاملLearning person-object interactions for action recognition in still images
We investigate a discriminatively trained model of person-object interactions for recognizing common human actions in still images. We build on the locally order-less spatial pyramid bag-of-features model, which was shown to perform extremely well on a range of object, scene and human action recognition tasks. We introduce three principal contributions. First, we replace the standard quantized ...
متن کاملAction recognition in still images by latent superpixel classification
Action recognition from still images is an important task of computer vision applications such as image annotation, robotic navigation, video surveillance and several others. Existing approaches mainly rely on either bag-of-feature representations or articulated body-part models. However, the relationship between the action and the image segments is still substantially unexplored. For this reas...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2018
ISSN: 1877-0509
DOI: 10.1016/j.procs.2018.10.432