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Hand Gesture Recognition is completed on top-view hand images observed by a Time of Flight(ToF) camera in a car. The work attempts to solve two important problems of touchless interactions inside a car. First, low latency identification of the gestures which are unobtrusive for the driver. Second, reducing the labelled data required to train learning based solutions, this is particularly important...
Learning based approaches have not yet achieved their full potential in optical flow estimation, where their performance still trails heuristic approaches. In this paper, we present a CNN based patch matching approach for optical flow estimation. An important contribution of our approach is a novel thresholded loss for Siamese networks. We demonstrate that our loss performs clearly better than existing...
This paper presents the design and development of STants, a low-cost, wearable system for monitoring lower body movements in long-term training sessions. Multiple miniaturized inertial measurement units (IMUs) are integrated into a pair of pants and socks using textile cables. This results in a lightweight and easy to use platform providing comfortableness and maximal movement flexibility for the...
In this paper a method for Early Recognition (ER) of Motion Templates (MTs) is presented. We define ER as an algorithm to provide recognition results before a motion sequence is completed. In our experiments we apply Long Short-Term Memory (LSTM) and optimize the training for the task of recognizing the motion template as early as possible. The evaluation has shown that the recognition accuracy for...
We present a robust real-time capable and simple framework for segmenting video sequences and live-streams of manual workflows into the comprising single tasks. Using classifiers trained on these segments we can follow a user that is performing the workflow in real-time as well as learn task variants from additional video examples. Our proposed method neither requires object detection nor high-level...
This paper proposes a novel method for automated generation of motion segmentation models for full body motion monitoring. The method generates, in an un-supervised manner, a motion template for a dynamic warping approach from a short training sequence, i.e., from very few data. Therefore it first automatically detects motif candidates, i.e. the recurring patterns in the training sequence. Then it...
This paper discusses several aspects and practical issues of physical activity recognition. Many existent activity recognition applications only include the few and well known basic activities, thus limiting the applicability of these systems. One of the main goals of this paper is to point out the importance of extending activity recognition with background activities, and to demonstrate its effects...
This paper addresses two fundamental requirements of full body motion monitoring: (a) the ability to sense the input of the user and (b) the means to interpret the captured input. Appropriate technology in both areas is required for an interactive virtual reality system to provide feedback in a useful and natural way. This paper combines technologies for both areas: It develops a sensor fusion approach...
Physical activity provides many physiological benefits. On the one hand it reduces the risk of disease outcomes. On the other hand it is the basis for proper rehabilitation in case of or after a severe disease. Both aspects are especially important for the elderly population. Within this context, the present paper proposes a personalized, home-based exercise trainer for elderly people. The system...
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