Detection of major ASL sign types in continuous signing for ASL recognition

In American Sign Language (ASL) as well as other signed languages, different classes of signs (e.g., lexical signs, fingerspelled signs, and classifier constructions) have different internal structural properties. Continuous sign recognition accuracy can be improved through use of distinct recognition strategies, as well as different training datasets, for each class of signs. For these strategies to be applied, continuous signing video needs to be segmented into parts corresponding to particular classes of signs. In this paper we present a multiple instance learning-based segmentation system that accurately labels 91.27% of the video frames of 500 continuous utterances (including 7 different subjects) from the publicly accessible NCSLGR corpus (Neidle and Vogler, 2012). The system uses novel feature descriptors derived from both motion and shape statistics of the regions of high local motion. The system does not require a hand tracker

A multistage hierarchical algorithm for hand shape recognition

This paper represents a multistage hierarchical algorithm for hand shape recognition using principal component analysis (PCA) as a dimensionality reduction and a feature extraction method. The paper discusses the effect of image blurring to build data manifolds using PCA and the different ways to construct these manifolds. In_order to classify the hand shape of an incoming sign object and to be invariant to linear transformations like translation and rotation, a multistage hierarchical classifier structure is used. Computer generated images for different Irish Sign Language shapes are used in testing. Experimental results are given to show the accuracy and performance of the proposed algorithm

Continuous sign recognition of brazilian sign language in a healthcare setting

Communication is the basis of human society. The majority of people communicate using spoken language in oral or written form. However, sign language is the primary mode of communication for deaf people. In general, understanding spoken information is a major challenge for the deaf and hard of hearing. Access to basic information and essential services is challenging for these individuals. For example, without translation support, carrying out simple tasks in a healthcare center such as asking for guidance or consulting with a doctor, can be hopelessly difficult. Computer-based sign language recognition technologies offer an alternative to mitigate the communication barrier faced by the deaf and hard of hearing. Despite much effort, research in this field is still in its infancy and automatic recognition of continuous signing remains a major challenge. This paper presents an ongoing research project designed to recognize continuous signing of Brazilian Sign Language (Libras) in healthcare settings. Health emergency situations and dialogues inspire the vocabulary of the signs and sentences we are using to contribute to the field301Vision-based human activity recognition8289COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESnão te

Continuous Action Recognition Based on Sequence Alignment

Continuous action recognition is more challenging than isolated recognition because classification and segmentation must be simultaneously carried out. We build on the well known dynamic time warping (DTW) framework and devise a novel visual alignment technique, namely dynamic frame warping (DFW), which performs isolated recognition based on per-frame representation of videos, and on aligning a test sequence with a model sequence. Moreover, we propose two extensions which enable to perform recognition concomitant with segmentation, namely one-pass DFW and two-pass DFW. These two methods have their roots in the domain of continuous recognition of speech and, to the best of our knowledge, their extension to continuous visual action recognition has been overlooked. We test and illustrate the proposed techniques with a recently released dataset (RAVEL) and with two public-domain datasets widely used in action recognition (Hollywood-1 and Hollywood-2). We also compare the performances of the proposed isolated and continuous recognition algorithms with several recently published methods

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

Sign Language and Computing in a Developing Country: A Research Roadmap for the Next Two Decades in the Philippines

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Overcoming the Newtonian Paradigm: The Unfinished Project of Theoretical Biology from a Schellingian Perspective

Defending Robert Rosen’s claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling’s demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive tradition of anti-reductionist biomathematics. It is shown that the mathematicoephysico echemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this antireductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics