0000000000113430
AUTHOR
Francisco Sanchez-fernandez
Phis-Lbp: Feature Descriptor for Vehicle Detection
International audience
Context-Aware Model Applied to Hog Descriptor for People Detection
International audience; This work proposes and implements a method based on Context-Aware Visual Attention Model (CAVAM), but modifying the method in such way that the detection algorithm is replaced by Histograms of Oriented Gradients (HOG). After reviewing different algorithms for people detection, we select HOG method because it is a very well known algorithm, which is used as a reference in virtually all current research studies about automatic detection. In addition, it produces accurate results in significantly less time than many algorithms. In this way, we show that CAVAM model can be adapted to other methods for object detection besides Scale-Invariant Feature Transform (SIFT), as …
Background subtraction for aerial surveillance conditions
International audience; The first step in a surveillance system is to create a representation of the environment. Background subtraction is widely used algorithm to define a part of an image that most time remains stationary in a video. In surveillance tasks, this model helps to recognize those outlier objects in an area under monitoring. Set up a background model on moving platforms (intelligent cars, UAVs, etc.) is a challenging task due camera motion when images are acquired. In this paper, we propose a method to support instabilities caused by aerial images fusing spatial and temporal information about image motion. We used frame difference as first approximation, then age of pixels is …
Dynamic management of reconfigurable logical computing areas: A real-time system for pedestrian detection in video
International audience
Multi-Scale Feature Extraction for Vehicle Detection Using Phis-Lbp
International audience; Multi-resolutionobjectdetectionfacesseveraldrawbacksincludingitshighdimensionalityproducedby a richer image representation in different channels or scales. In this paper, we propose a robust and lightweight multi-resolution method for vehicle detection using local binary patterns (LBP) as channel feature. Algorithm acceleration is done using LBP histograms instead of multi-scale feature maps and by extrapolating nearby scales to avoid computing each scale. We produce a feature descriptor capable of reaching a similar precision to other computationally more complex algorithms but reducing its size from 10 to 800 times. Finally, experiments show that our method can obt…
A2Ba: Adaptive Background Modelling for Visual Aerial Surveillance Conditions
International audience; Background modelling algorithms are widely used to define a part of an image that most time remains stationary in a video. In surveillance tasks, this model helps to recognize those outlier objects in an area under monitoring. Set up a background model on mobile platforms (UAVs, intelligent cars, etc.) is a challenging task due camera motion when images are acquired. In this paper, we propose A2Ba, a robust method to support instabilities caused by aerial images fusing different information about image motion. We used frame difference as first approximation, then age of pixels is estimated. This latter gives us an invariability level of a pixel over time. Gradient di…