Presentation + Paper
16 May 2018 Plenoptic imaging techniques for improving accuracy and robustness of object tracking
Dae Hyun Bae, Jae Woo Kim, Hae Chan Noh, Do Hyung Kim, Jae-Pil Heo
Author Affiliations +
Abstract
Object tracking is a core technique in many computer vision applications. The problem becomes especially challenging when the target object is fully or even partially occluded. A recent work has shown the feasibility of utilizing plenoptic imaging techniques to resolve such occlusion problems. Specifically, it constructs focal stacks from plenoptic image sequences and selects an optimal image sequences from the stacks that can maximize the tracking accuracy. Even though the technique has proven the merit of using plenoptic images in the object tracking, there is still room for improvement. In this paper, we propose two simple but effective algorithms to improve both accuracy and robustness of object tracking based on plenoptic images. We first propose to use an image sharpening technique to reduce the blur that the refocused images inheritably have. The image sharpening makes the shape of objects more distinct, and thus a higher accuracy in the object tracking can be achieved. We also propose an adaptive bounding box proposal algorithm to overcome difficult cases where the size of the target object in the image space drastically changes. This improves the robustness in the object tracking compared to prior techniques which assumed fixed sized objects. We validate our proposed algorithms on two different scenarios, and the experimental results confirm the benefit of our method.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dae Hyun Bae, Jae Woo Kim, Hae Chan Noh, Do Hyung Kim, and Jae-Pil Heo "Plenoptic imaging techniques for improving accuracy and robustness of object tracking", Proc. SPIE 10666, Three-Dimensional Imaging, Visualization, and Display 2018, 106660H (16 May 2018); https://doi.org/10.1117/12.2306768
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KEYWORDS
Cameras

Detection and tracking algorithms

Image processing

3D image processing

Imaging systems

Data acquisition

Image resolution

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