Ahmet Alp Kindiroglu

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This paper presents a framework for spotting and recognizing continuous human gestures. Skeleton based features are extracted from normalized human body coordinates to represent gestures. These features are then used to construct spatio-temporal template based Random Decision Forest models. Finally, predictions from different models are fused at score level(More)
Supervised Descent Method (SDM) has proven successful in many computer vision applications such as face alignment, tracking and camera calibration. Recent studies which used SDM, achieved state of the-art performance on facial landmark localization in depth images [4]. In this study, we propose to use ridge regression instead of least squares regression for(More)
This paper presents the design and evaluation of a multi-lingual fingerspelling recognition module that is designed for an information terminal. Through the use of multimodal input and output methods, the information terminal acts as a communication medium between deaf and blind people. The system converts fingerspelled words to speech and vice versa using(More)
The aim of this paper is to help the communication of two people, one hearing impaired and one visually impaired by converting speech to fingerspelling and finger-spelling to speech. Fingerspelling is a subset of sign language , and uses finger signs to spell letters of the spoken or written language. We aim to convert finger spelled words to speech and(More)
In this study, we investigate the techniques to automatically predict the extraversion trait among the Big Five personality traits (Openness to Experience, Conscientiousness, Extraversion, Agreableness, Emotional Stability) using visual nonverbal cues in small group meetings. Our aim is to increase the prediction accuracy by transferring the knowledge that(More)
There are as many sign languages as there are deaf communities in the world. Linguists have been collecting corpora of different sign languages and annotating them extensively in order to study and understand their properties. On the other hand, the field of computer vision has approached the sign language recognition problem as a grand challenge and(More)
In this paper, we present a fingerspelling recognition module that has been designed to function in a smart system that is intended to act as a communication medium between people with hearing and visual disabilities. The method described is a computer vision based, close to real-time, automatic skin color based model hand gesture recognition module. We(More)
Gesture recognition is becoming popular as an efficient input method for human computer interaction. However, challenges associated with data collection, data annotation, maintaining standardization, and the high variance of data obtained from different users in different environments make developing such systems a difficult task. The purpose of this study(More)