Niki Aifanti - Academia.edu (original) (raw)

Papers by Niki Aifanti

Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003

posture by maximizing the similarity between the projected 3 0 model and the segmented image. Exp... more posture by maximizing the similarity between the projected 3 0 model and the segmented image. Experimental results with video sequences are presented.

Series in Machine Perception and Artificial Intelligence, 2009

This paper presents a new approach for human walking modeling from monocular image sequences. A k... more This paper presents a new approach for human walking modeling from monocular image sequences. A kinematics model and a walking motion model are introduced in order to exploit prior knowledge. The proposed technique consists of two steps. Initially, an efficient feature point selection and tracking approach is used to compute feature points' trajectories. Peaks and valleys of these trajectories are used to detect key framesframes where both legs are in contact with the floor. Secondly, motion models associated with each joint are locally tuned by using those key frames. Differently than previous approaches, this tuning process is not performed at every frame, reducing CPU time. In addition, the movement's frequency is defined by the elapsed time between two consecutive key frames, which allows handling walking displacement at different speed. Experimental results with different video sequences are presented.

Lecture Notes in Computer Science, 2004

This paper presents a new approach for 3D human walking modeling from monocular image sequences. ... more This paper presents a new approach for 3D human walking modeling from monocular image sequences. An efficient feature point selection and tracking approach has been used to compute feature points' trajectories. Peaks and valleys of these trajectories are used to detect key frames-frames where both legs are in contact with the floor. These frames, together with prior knowledge of body kinematics and a motion model, are the basis for the 3D reconstruction of human walking. The legs' configuration at each key frame contributes to tune the amplitude of the motion model. Differently than previous approaches, this tuning process is not performed at every frame, reducing CPU time. In addition, the movement's frequency is defined by the elapsed time between two consecutive key frames, which allows handling walking displacement at different speed. Experimental results with different video sequences are presented. 1 F.

Synthesis and Analysis Techniques for the Human Body, 2006

Abstract The problem of human body modeling was initially tackled to solve applications related t... more Abstract The problem of human body modeling was initially tackled to solve applications related to the film industry or computer games within the computer graphics (CG) community. Since then, several different tools were developed for editing and animating 3D digital body models. Although at the beginning most of those tools were devised within the computer graphics community, nowadays a lot of work proceeds from the computer vision (CV) community. In spite of this overlapped interest, there is a considerable difference between ...

2004 International Conference on Image Processing, 2004. ICIP '04., 2004

This paper presents a new approach for 3D gait estimation from monocular image sequences, using b... more This paper presents a new approach for 3D gait estimation from monocular image sequences, using both a kinematics and a walking motion models as sources of prior knowledge. The proposed technique consists of two major stages. Firstly, the motion trajectory and the pedestrian's footprints are detected throughout the segmented video sequence. Secondly, as the 3D human model, driven by the prior motion model, walks over this trajectory, the joints' angles are locally adjusted to the pedestrian's walking style. This tuning process is performed once per walking cycle and not per frame, saving considerable CPU time. In addition, local tuning allows handling displacements at different speeds or directions. The target application is the augmentation of 2D television sequences with depth information that may be used in future 3D-TV systems.

This chapter presents a survey of the most recent vision-based human body modeling techniques. It... more This chapter presents a survey of the most recent vision-based human body modeling techniques. It includes sections covering the topics of 3D human body coding standards, motion tracking, recognition and applications. Short summaries of various techniques, including their advantages and disadvantages, are introduced. Although this work is focused on computer vision, some references from computer graphics are also given. Considering

Signal Processing: Image Communication, 2014

IEEE Transactions on Information Forensics and Security, 2006

In this paper, a biometric authentication system based on measurements of the user's three-dimens... more In this paper, a biometric authentication system based on measurements of the user's three-dimensional (3-D) hand geometry is proposed. The system relies on a novel real-time and low-cost 3-D sensor that generates a dense range image of the scene. By exploiting 3-D information we are able to limit the constraints usually posed on the environment and the placement of the hand, and this greatly contributes to the unobtrusiveness of the system. Efficient, close to real-time algorithms for hand segmentation, localization and 3-D feature measurement are described and tested on an image database simulating a variety of working conditions. The performance of the system is shown to be similar to state-of-the-art hand geometry authentication techniques but without sacrificing the convenience of the user.