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Machine vision technologies hold the promise of enabling rapid and accurate fruit crop yield predictions in the field. The key to fulfilling this promise is accurate segmentation and detection of fruit in images of tree canopies. This paper proposes two new methods for automated counting of fruit in images of mango tree canopies, one using texture-based dense segmentation and one using shape-based...
Through automated agricultural inspection, farmers can potentially achieve better productivity and accurately predict yields and crop quality. A variety of sensors can be used for agricultural inspection, but the cheapest and most information-rich is the video camera. We collect data in the field from a monocular camera fixed to a mobile inspection platform. For purposes of pineapple crop mapping...
Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. Because of high levels of occlusion, dense features, and shadows, object detectors tend to produce large numbers of false detections. We introduce a new method based on 3D head plane estimation that reduces these false detections...
This paper presents the results of a series of three experiments carried out to evaluate the speed and accuracy of target acquisition tasks using visual, auditory, or tactile feedback modalities. Ten participants conducted a series of 1-D and 2-D pointing tasks using a pen-based input device and either visual, audio or tactile (vibratory) feedback. Fitts' Law was used to analyze the results. Overall,...
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