Higher order local autocorrelation features of PARCOR images for gesture recognition

نویسندگان

  • Takio Kurita
  • Yasuo Kobayashi
  • Taketoshi Mishima
چکیده

This paper proposes a feature extraction method for gesture recognition, which is based on higher order local autocorrelation (HLAC) of PARCOR images. To extract dominant information from a sequence of images, we apply linear prediction coding technique to the sequence of pixel values and PARCOR images are constructed from the PARCOR coe cients of the sequences of the pixel values. Then HLAC features, which are inherently shift-invariant and computationally inexpensive, are extracted from the PARCOR images. Thus the proposed features become robust to changes of shift of the person's position. Experimental results of gesture recognition are shown to evaluate the performance of the proposed features.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Gesture Recognition Using HLAC Features of PARCOR Images and HMM Based Recognizer

This paper proposes a gesture recognition method which uses higher order local autocorrelation (HLAC) features extracted from PARCOR images. To extract dominant information from a sequence of images, we apply linear prediction coding technique to the sequence of pixel values and PARCOR images are constructed from the PARCOR coe cients of the sequences of the pixel values. From the PARCOR images...

متن کامل

Gesture Recognition using HLAC Features of PARCOR

This paper proposes a gesture recognition method which uses higher order local autocorrelation (HLAC) features extracted from PARCOR images. To extract dominant information from a sequence of images, we apply linear prediction coding technique to the sequence of pixel intensities and PARCOR images are constructed from the PARCOR coe cients of the sequences of the pixel values. From the PARCOR i...

متن کامل

Image representation for generic object recognition using higher-order local autocorrelation features on posterior probability images

This paper presents a novel image representation method for generic object recognition by using higher-order local autocorrelations on posterior probability images. The proposed method is an extension of the bag-of-features approach to posterior probability images. The standard bag-of-features approach is approximately thought of as a method that classifies an image to a category whose sum of p...

متن کامل

Hand Gesture Recognition from RGB-D Data using 2D and 3D Convolutional Neural Networks: a comparative study

Despite considerable enhances in recognizing hand gestures from still images, there are still many challenges in the classification of hand gestures in videos. The latter comes with more challenges, including higher computational complexity and arduous task of representing temporal features. Hand movement dynamics, represented by temporal features, have to be extracted by analyzing the total fr...

متن کامل

A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis

This paper proposes a new scheme for multipurpose image recognition based on Higher-order Local AutoCorrelation (HLAC) features and factor analysis. First, HLAC features, which are inherently invariant under translation, computationally inexpensive, and additive, are extracted from the input images. Second, factor analysis is applied to the feature vectors so as to decompose the feature vectors...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1997