Frédéric Suard

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This paper presents a complete method for pedestrian detection applied to infrared images. First, we study an image descriptor based on histograms of oriented gradients (HOG), associated with a support vector machine (SVM) classifier and evaluate its efficiency. After having tuned the HOG descriptor and the classifier, we include this method in a complete(More)
This paper details filtering subsystem for a tetra-vision based pedestrian detection system. The complete system is based on the use of both visible and far infrared cameras; in an initial phase it produces a list of areas of attention in the images which can contain pedestrians. This list is furtherly refined using symmetry-based assumptions. Then, this(More)
This paper presents a method for object categorization. This problem is difficult and can be solved by combining different information sources such as shape or appearance. In this paper, we aim at performing object recognition by mixing kernels obtained from different cues. Our method is based on two complementary descriptions of an object. First, we(More)
A common approach for classifying shock graphs is to use a dissimilarity measure on graphs and a distance based classifier. In this paper, we propose the use of kernel functions for data mining problems on shock graphs. The first contribution of the paper is to extend the class of graph kernel by proposing kernels based on bag of paths. Then, we propose a(More)
This paper presents a method for pedestrian detection with stereovision and graph comparison. Images are segmented thanks to the NCut method applied on a single image, and the disparity is computed from a pair of images. This segmentation enables us to keep only shapes of potential obstacles, by eliminating the background. The comparison between two graphs(More)
A common approach for classifying shock graphs is to use a dissimilarity measure on graphs and a distance based classifier. In this paper, we propose the use of kernel functions for data mining problems on shock graphs. The first contribution of the paper is to extend the class of graph kernel by proposing kernels based on bag of paths. Then, we propose a(More)
This paper presents a pedestrian detection method based on the multiple kernel framework. This approach enables us to select and combine different kinds of image representations. The combination is done through a linear combination of kernels, weighted according to the relevance of kernels. After having presented some descriptors and detailed the multiple(More)
Article history: Received 26 June 2015 Received in revised form 16 October 2015 Accepted 5 December 2015 Available online 23 December 2015 The overall energy efficiency of existing buildings has to be significantly improved to complywith emerging regulations and to contribute to overcoming current environmental challenges. Many policies aim at accelerating(More)
A chemometric method based on an hypothesis test approach built upon RLS (Recursive Least Square) algorithm is presented. This method offers an alternative for online recognition: each analyzed sample leads to the convergence of the system to a state characteristic of the presence of a chemical compound. We present how hypothesis tests are used to exploit(More)