Audio imaging can play a fundamental role in computer vision, in particular in automated surveillance, boosting the accuracy of current systems based on standard optical cameras. We present here a method for object tracking application that fuses visual image with an audio image in the template-matching framework. Firstly, an improved template matching based tracking is presented that takes care of the chaotic movements in the template-matching algorithm. Then a fusion scheme is presented that makes use of deviations in the correlation scores pattern obtained across the individual frame in each imaging domain. The method is compared with various state of art trackers that perform track estimation using only visible imagery. Results highlight a significant improvement in the object tracking by the assistance of audio imaging using the proposed method under severe challenging vision conditions such as occlusions, object shape deformations, the presence of clutters and camouflage, etc.

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The current paper proposes recognition of partially invisible objects in images using image enhancement techniques. The problem mainly arises in night vision images which comprise poor contrast standards. Also during daytime, the object which is captured under sunlight is the lone survivor and the rest of information is not captured by camera properly. Image enhancement techniques to improve visual quality have been popularized with the proliferation of digital imagery and computers. Histogram Equalization (HE) is a versatile image improvement technique that can be incorporated for converting the partial visible objects/invisible objects into a proper vision. Further for enriching the information in image obtained by the HE image, a Contrast Limited Adaptive Histogram Equalization (CLAHE) is incorporated and finally for smoothing purpose, the image thus obtained is passed through a Gaussian filter. Results on various set of images show that above two techniques HE and CLAHE along with a Gaussian filter significantly improve the quality of image and hence assist to discover the partially visible/invisible objects.

Recently there has been an increase in the use of thermal-visible conjunction technique in the field of surveillance applications due to complementary advantages of both. An amalgamation of these for tracking requires a reasonable scientific procedure that can efficiently make decisions with sound accuracy and excellent precision. The proposed research presents a unique idea for obtaining a robust track estimate with the thermo-visual fusion in the context of fundamental template matching. This method firstly introduces a haphazard transporting control mechanism for individual modality tracking that avoids unexpected estimates. Then it brings together an efficient computation procedure for providing the weighted output using minimal information from the individual trackers. Experiments performed on publically available datasets mark the usefulness of the proposed idea in the context of accuracy, precision and process time in comparison with the state of art methods.

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