Proceedings ArticleDOI
Performance evaluation of object detection and tracking method under illumination variation
Naimish Kasundra,Krishna K. Warhade +1 more
- pp 1-6
TLDR
Experiments shows that proposed discrete wavelet transform based method has a high capability to detect and track non-rigid moving object, even when light intensities change abruptly.Abstract:
A robust, meticulous and high performance approach is still a great challenge in tracking approach. There are various difficulties in object tracking like noise in scene, illumination changes, occlusion effect, and pose variation into the scene. As an object moves, it changes its orientation relative to the light sources which illuminate it. An illumination variation causes tracking algorithm to lose the target in the scene. This paper presents a discrete wavelet transform based method of detecting and tracking moving object under varying illumination condition with a stationary camera. Discrete wavelet transform provides illumination invariant feature extraction method using gaussian smoothing function and thresholding. We have tested tracking results, on number of video sequences with indoor and outdoor environments and demonstrated the effectiveness of our proposed method. Experiments shows that proposed method has a high capability to detect and track non-rigid moving object, even when light intensities change abruptly.read more
Citations
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Development of deep learning-based equipment heat load detection for energy demand estimation and investigation of the impact of illumination
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Research on Vehicle Detection and Tracking Algorithm Based on the Methods of Frame Difference and Adaptive Background Subtraction Difference
TL;DR: Experimental result shows that the improving algorithm can extract all moving objects, which was endowed with strong background adaptability and better real-time performance.
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Evaluation of the detection ability of a multi-sensor system under weak light
TL;DR: An evaluation method that uses the response characteristics of lidar, depth camera, and RGB camera to the surrounding environment, takes the surface illuminance and BRDF of the target as input variables, and uses the minimum distance classification method to realize the lateral evaluation and comparison of different sensors is proposed.
References
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Journal ArticleDOI
Illumination invariant stationary object detection
TL;DR: Experimental results have shown that the tracking technique gives more than a 95% detection success rate, even if objects are partially occluded, and the results obtained are compared with other available state-of-the-art methods.
Proceedings ArticleDOI
Moving object tracking - a parametric edge tracking approach
TL;DR: Experiments show that the proposed edge-segment based tracking algorithm can track moving objects efficiently under varying illumination conditions.
Journal ArticleDOI
Object Tracking Using Maximum Colour Distance Under Illumination Change
TL;DR: A new method for tracking moving objects that have colour variations due to illumination, which uses a maximum colour distance on the mean shift framework to provide robust real-time object tracking with large colour variation in objects whose colour changes due to external illumination.