Search results for " pattern"
showing 10 items of 2245 documents
Motion Analysis for Dynamic 3D Scene Reconstruction and Understanding
2017
This thesis studies the problem of dynamic scene 3D reconstruction and understanding using a calibrated 2D-3D camera setup mounted on a mobile platform via the analysis of objects' motions. For static scenes, the sought 3D map reconstruction can be obtained by registering the point cloud sequence. However, with dynamic scenes, we require a prior step of moving object elimination, which yields to the motion detection and segmentation problems. We provide solutions for the two practical scenarios, namely the known and unknown camera motion cases, respectively. When camera motion is unknown, our 3D-SSC and 3D-SMR algorithms segment the moving objects by analysing their 3D feature trajectories.…
Motion analysis using the novelty filter
1991
Abstract An original approach to the motion analysis, based on the novelty filter, is proposed. The novelty filter stresses the novelties occurring in a pattern representing an image of the scene under consideration with respect to patterns representing previous images of the same scene, so that visual information about the motion of the objects is obtained. The novelty filter may be implemented by a neural network architecture, taking advantage of the capabilities of massive parallelism, adaptive learning and noise robustness. The novelty filter may learn the entire trajectory of an object, through an incremental learning of a sequence of images capturing the scene, thus emphasizing if the…
Speckle-based configuration for simultaneous in vitro inspection of mechanical contractions of cardiac myocyte cells.
2013
An optical lensless configuration for a remote noncontact measuring of mechanical contractions of a vast number of cardiac myocytes is proposed. All the myocytes were taken from rats, and the measurements were done in an in vitro mode. The optical method is based on temporal analysis of secondary reflected speckle patterns generated in lensless microscope configuration. The processing involves analyzing the movement and the change in the statistics of the secondary speckle patterns that are created on top of the cell culture when it is illuminated by a spot of laser beam. The main advantage of the proposed system is the ability to measure many cells simultaneously (∼1000 cells) and to extra…
How a Fish’s Brain May Move a Fish’s Body
1990
The brainstem of the electric fish Eigenmannia virescens contains a small number of neural networks projecting directly onto the motoneuron pools of the spinal cord such that each segment is reached by at least one neuron of all the networks. Quantitative data of movement patterns, recorded from freely moving animals as well as elicited by electrical stimulation of the single networks, suggest that each network contains a full program for a particular movement, e. g. bending of the body axis to one side. By virtue of the structural relationship the programs are executable with a small number of segments. Mixing of small pieces of programs along the body axis allows for a far larger variety …
Revealing the unique features of each individual's muscle activation signatures
2021
International audience; There is growing evidence that each individual has unique movement patterns, or signatures. The exact origin of these movement signatures, however, remains unknown. We developed an approach that can identify individual muscle activation signatures during two locomotor tasks (walking and pedalling). A linear support vector machine was used to classify 78 participants based on their electromyographic (EMG) patterns measured on eight lower limb muscles. To provide insight into decision-making by the machine learning classification model, a layer-wise relevance propagation (LRP) approach was implemented. This enabled the model predictions to be decomposed into relevance …
A label compression method for online multi-label classification
2018
Abstract Many modern applications deal with multi-label data, such as functional categorizations of genes, image labeling and text categorization. Classification of such data with a large number of labels and latent dependencies among them is a challenging task, and it becomes even more challenging when the data is received online and in chunks. Many of the current multi-label classification methods require a lot of time and memory, which make them infeasible for practical real-world applications. In this paper, we propose a fast linear label space dimension reduction method that transforms the labels into a reduced encoded space and trains models on the obtained pseudo labels. Additionally…
A comprehensive survey of multi-view video summarization
2021
[EN] There has been an exponential growth in the amount of visual data on a daily basis acquired from single or multi-view surveillance camera networks. This massive amount of data requires efficient mechanisms such as video summarization to ensure that only significant data are reported and the redundancy is reduced. Multi-view video summarization (MVS) is a less redundant and more concise way of providing information from the video content of all the cameras in the form of either keyframes or video segments. This paper presents an overview of the existing strategies proposed for MVS, including their advantages and drawbacks. Our survey covers the genericsteps in MVS, such as the pre-proce…
Studying the evolution of neural activation patterns during training of feed-forward ReLU networks
2021
The ability of deep neural networks to form powerful emergent representations of complex statistical patterns in data is as remarkable as imperfectly understood. For deep ReLU networks, these are encoded in the mixed discrete–continuous structure of linear weight matrices and non-linear binary activations. Our article develops a new technique for instrumenting such networks to efficiently record activation statistics, such as information content (entropy) and similarity of patterns, in real-world training runs. We then study the evolution of activation patterns during training for networks of different architecture using different training and initialization strategies. As a result, we see …
On Spatio-Temporal Saliency Detection in Videos using Multilinear PCA
2016
International audience; Visual saliency is an attention mechanism which helps to focus on regions of interest instead of processing the whole image or video data. Detecting salient objects in still images has been widely addressed in literature with several formulations and methods. However, visual saliency detection in videos has attracted little attention, although motion information is an important aspect of visual perception. A common approach for obtaining a spatio-temporal saliency map is to combine a static saliency map and a dynamic saliency map. In this paper, we extend a recent saliency detection approach based on principal component analysis (PCA) which have shwon good results wh…
A Neural Network-Based Algorithm for 3D Multispectral Scanning Applied to Multimedia
2005
We describe a new stereoscopic system based on a multispectral camera and an LCD-Projector. The novel concept we want to show consists in the use of multispectral information for 3D-scenes reconstruction. Each 3D point is linked to a curve representing the spectral reflectance. This latter is a physical representation of the matter and presents the advantage over color information, which is perceptual, that it is independent from both illuminant and observer. We first present an easy methodology to geometrically and spectrally calibrate such a system. We then describe an algorithm for recovering 3D coordinates based on triangulation and an algorithm for reflectance curves reconstruction bas…