A cellular automata based approach to track salient objects in videos

In this paper we present an algorithm to track the motion of a salient object using Cellular Automata (CA). The overall work, taking inspiration from recent research on insect sensory motor system, investigates the application of non conventional computer vision approaches to evaluate their effectiveness in fulfilling this task. The proposed system employs the Sobel operator to individual frames, performing further elaborations through a CA, with the aim of detecting and characterizing moving entities within the field of view to support collision avoidance from the perspective of the viewer. The paper formally describes the adopted approach as well as its experimentation videos representing plausible situations.

[1]  Huchuan Lu,et al.  Saliency detection via Cellular Automata , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  F Gabbiani,et al.  Collision-avoidance behaviors of minimally restrained flying locusts to looming stimuli , 2013, Journal of Experimental Biology.

[3]  Georgios Ch. Sirakoulis,et al.  An Edge Preserving Image Resizing Method Based on Cellular Automata , 2012, ACRI.

[4]  Philippe Lucas,et al.  Reactive Searching and Infotaxis in Odor Source Localization , 2014, PLoS Comput. Biol..

[5]  Andrés Manuel García,et al.  Cellular automata models for the simulation of real-world urban processes: A review and analysis , 2010 .

[6]  Georgios Ch. Sirakoulis,et al.  An FPGA implemented cellular automaton crowd evacuation model inspired by the electrostatic-induced potential fields , 2010, Microprocess. Microsystems.

[7]  Herbert Freeman,et al.  Machine Vision for Three-Dimensional Scenes , 1990 .

[8]  Manfred Hartbauer,et al.  Simplified bionic solutions: a simple bio-inspired vehicle collision detection system , 2017, Bioinspiration & biomimetics.

[9]  Giancarlo Mauri,et al.  Neuro-Radiosurgery Treatments: MRI Brain Tumor Seeded Image Segmentation Based on a Cellular Automata Model , 2016, ACRI.

[10]  Irwin Sobel,et al.  An Isotropic 3×3 image gradient operator , 1990 .

[11]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Massimo Vergassola,et al.  ‘Infotaxis’ as a strategy for searching without gradients , 2007, Nature.

[13]  Lawrence G. Roberts,et al.  Machine Perception of Three-Dimensional Solids , 1963, Outstanding Dissertations in the Computer Sciences.

[14]  Bastien Chopard,et al.  Cellular Automata Modeling of Physical Systems , 1999, Encyclopedia of Complexity and Systems Science.

[15]  Lei Huang,et al.  Video salient object detection via cross-frame cellular automata , 2017, 2017 IEEE International Conference on Multimedia and Expo (ICME).

[16]  Philippe Lucas,et al.  Heterogeneity and Convergence of Olfactory First-Order Neurons Account for the High Speed and Sensitivity of Second-Order Neurons , 2014, PLoS Comput. Biol..

[17]  Ryohei Kanzaki,et al.  Using insects to drive mobile robots - hybrid robots bridge the gap between biological and artificial systems. , 2017, Arthropod structure & development.

[18]  Tommaso Toffoli,et al.  Cellular automata machines - a new environment for modeling , 1987, MIT Press series in scientific computation.

[19]  Rachid Deriche,et al.  Using Canny's criteria to derive a recursively implemented optimal edge detector , 1987, International Journal of Computer Vision.

[20]  Ryohei Kanzaki,et al.  A simple behaviour provides accuracy and flexibility in odour plume tracking – the robotic control of sensory-motor coupling in silkmoths , 2015, Journal of Experimental Biology.

[21]  Stephen Wolfram,et al.  Cellular automata as models of complexity , 1984, Nature.

[22]  Chun-Ling Chang,et al.  Cellular automata for edge detection of images , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[23]  Stefania Bandini,et al.  Motion Detection and Characterization in Videos with Cellular Automata , 2018, ACRI.

[24]  Shai Avidan,et al.  Support vector tracking , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Stefania Bandini,et al.  An Approach for Managing Heterogeneous Speed Profiles in Cellular Automata Pedestrian Models , 2017, Journal of Cellular Automata.

[26]  P. V. Arun,et al.  Comparative analysis of common edge detection techniques in context of object extraction , 2014, ArXiv.

[27]  Gadadhar Sahoo,et al.  A Novel Method of Edge Detection using Cellular Automata , 2010 .

[28]  Fabrizio Gabbiani,et al.  Collision detection as a model for sensory-motor integration. , 2011, Annual review of neuroscience.

[29]  Georgios Ch. Sirakoulis,et al.  Cellular automata on FPGA for real-time urban traffic signals control , 2013, The Journal of Supercomputing.