Conference Paper

Hand Gesture Recognition for Human-Machine Interaction.

Source: DBLP

ABSTRACT Even after more than two decades of input devices development, many people still find the interaction with computers an uncomfortable experience. Efforts should be made to adapt computers to our natural means of communication: speech and body language. The PUI paradigm has emerged as a post-WIMP interface paradigm in order to cover these preferences. The aim of this paper is the proposal of a real time vision system for its application within visual interaction environments through hand gesture recognition, using general-purpose hardware and low cost sensors, like a simple personal computer and an USB web cam, so any user could make use of it in his office or home. The basis of our approach is a fast segmentation process to obtain the moving hand from the whole image, which is able to deal with a large number of hand shapes against different backgrounds and lighting conditions, and a recognition process that identifies the hand posture from the temporal sequence of segmented hands. The most important part of the recognition process is a robust shape comparison carried out through a Hausdorff distance approach, which operates on edge maps. The use of a visual memory allows the system to handle variations within a gesture and speed up the recognition process through the storage of different variables related to each gesture. This paper includes experimental evaluations of the recognition process of 26 hand postures and it discusses the results. Experiments show that the system can achieve a 90% recognition average rate and is suitable for real-time applications.

0 Bookmarks
 · 
116 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a CMOS imager consisting of 32×32 smart pixels, each one able to detect single photons in the 300-900 nm wavelength range and to perform both photon-counting and photon-timing operations on very fast optical events with faint intensities. In photon-counting mode, the imager provides photon-number (i.e, intensity) resolved movies of the scene under observation, up to 100 000 frames/s. In photon-timing, the imager provides photon arrival times with 312 ps resolution. The result are videos with either time-resolved (e.g., fluorescence) maps of a sample, or 3-D depth-resolved maps of a target scene. The imager is fabricated in a cost-effective 0.35-μm CMOS technology, automotive certified. Each pixel consists of a single-photon avalanche diode with 30 μm photoactive diameter, coupled to an in-pixel 10-bit time-to-digital converter with 320-ns full-scale range, an INL of 10% LSB and a DNL of 2% LSB. The chip operates in global shutter mode, with full frame times down to 10 μs and just 1-ns conversion time. The reconfigurable imager design enables a broad set of applications, like time-resolved spectroscopy, fluorescence lifetime imaging, diffusive optical tomography, molecular imaging, time-of-flight 3-D ranging and atmospheric layer sensing through LIDAR.
    IEEE Journal of Selected Topics in Quantum Electronics 09/2014; 20(6). · 4.08 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A novel method of dynamic hand gesture recognition based on Speeded Up Robust Features (SURF) tracking is proposed. The main characteristic is that the dominant movement direction of matched SURF points in adjacent frames is used to help describing a hand trajectory without detecting and segmenting the hand region. The dynamic hand gesture is then modeled by a series of trajectory direction data streams after time warping. Accordingly, the data stream clustering method based on correlation analysis is developed to recognize a dynamic hand gesture and to speed up calculation. The proposed algorithm is tested on 26 alphabetical hand gestures and yields a satisfactory recognition rate which is 87.1% on the training set and 84.6% on the testing set.
    Jiqiren/Robot 07/2011; 33(4).
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Gesture recognition techniques are used in order to achieve spontaneous and natural machine interactions. Normal Hand gesture based recognition techniques using single 2D camera have serious issues in terms of correct tracking; also the false recognition occurrences are higher. In this paper, we present an efficient method of implementing gesture recognition using marker. In this approach we use a single marker for gesture recognition by doing mouse emulation. Tracking is accurate and false recognition occurrences are found to be very low in this method. Also this approach is found to be computationally efficient and better user experience compared to other hand gesture recognition techniques using single 2D camera.
    International Journal of Computer Applications. 11/2013; 81(1):11-15.

Full-text

Download
0 Downloads
Available from