3-D gesture-based scene navigation in medical imaging applications using Time-of-Flight cameras

Soutschek, Stefan; Penne, Jochen; Hornegger, Joachim; Kornhuber, Johannes

doi:10.1109/cvprw.2008.4563162

Cited by 88 publications

(73 citation statements)

References 6 publications

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“…Either the range of application was limited or the performance results were dissatisfying. Usually a good performance result was achieved with a very limited pose set or if designed for a specific application [3]. ToF-Sensors -although working at stereo-frame rate -generally suffer from a low resolution which of course makes it difficult to extract proper features.…”

Section: Related Workmentioning

confidence: 99%

Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors

Kopinski

Gepperth

Geisler

et al. 2014

Artificial Neural Networks and Machine Learning – ICANN 2014

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Abstract. We present a study on 3D based hand pose recognition using a new generation of low-cost time-of-flight(ToF) sensors intended for outdoor use in automotive human-machine interaction. As signal quality is impaired compared to Kinect-type sensors, we study several ways to improve performance when a large number of gesture classes is involved. We investigate the performance of different 3D descriptors, as well as the fusion of two ToF sensor streams. By basing a data fusion strategy on the fact that multilayer perceptrons can produce normalized confidences individually for each class, and similarly by designing information-theoretic online measures for assessing confidences of decisions, we show that appropriately chosen fusion strategies can improve overall performance to a very satisfactory level. Real-time capability is retained as the used 3D descriptors, the fusion strategy as well as the online confidence measures are computationally efficient.

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Section: Related Workmentioning

confidence: 99%

Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors

Kopinski

Gepperth

Geisler

et al. 2014

Artificial Neural Networks and Machine Learning – ICANN 2014

View full text Add to dashboard Cite

show abstract

“…Existing prototypes use different concepts such as mapping the hand position to the position of the mouse pointer and using clicking gestures [70,72]. Other systems analyze gestures of the fingers [71,73], the hands [73,75,74,76,79] or analyze the hand position w.r.t. the body [76].…”

Section: Touch-less Interaction In Sterile Environmentsmentioning

confidence: 99%

“…However, these solutions either require hardware or markers to be worn by the user, or are less robust. In the last decade, several systems for touch-less interaction using stereo cameras [70], ToF imaging [71] and recently Microsoft Kinect [72,73,74,75,76,77] have been proposed. A commercially available system using infrared stereo cameras to access patient records in the OR is offered by Karl Storz GmbH, Tuttlingen, Germany [78].…”

Section: Touch-less Interaction In Sterile Environmentsmentioning

confidence: 99%

Real-Time Range Imaging in Health Care: A Survey

Bauer

Seitel

Hofmann³

et al. 2013

Lecture Notes in Computer Science

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Abstract. The recent availability of dynamic, dense, and low-cost range imaging has gained widespread interest in health care. It opens up new opportunities and has an increasing impact on both research and commercial activities. This chapter presents a state-of-the-art survey on the integration of modern range imaging sensors into medical applications. The scope is to identify promising applications and methods, and to provide an overview of recent developments in this rapidly evolving domain. The survey covers a broad range of topics, including guidance in computer-assisted interventions, operation room monitoring and workflow analysis, touch-less interaction and on-patient visualization, as well as prevention and support in elderly care and rehabilitation. We put emphasis on dynamic and interactive tasks where real-time and dense 3-D imaging forms the key aspect. While considering different range imaging modalities that fulfill these requirements, we particularly investigate the impact of Time-of-Flight imaging in this domain. Eventually, we discuss practical demands and limitations, and open research issues and challenges that are of fundamental importance for the progression of the field.

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“…Examples include geometric reconstruction of static scenes (Huhle et al, 2008), building of 3D maps for mobile applications and robotics (May et al, 2009), interaction control, e.g. for touch-free navigation for 3D medical visualization (Soutschek et al, 2008) as well as image segmentation , e.g. used for AR applications (Koch et al, 2009).…”

Section: State-of-the-artmentioning

confidence: 99%

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

Maier-Hein

Mountney

Bartoli

et al. 2013

Medical Image Analysis

242

130

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One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon's navigation capabilites by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D optical imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions.

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3-D gesture-based scene navigation in medical imaging applications using Time-of-Flight cameras

Abstract: For a lot of applications, and particularly for medical intra-operative applications, the exploration of and navigation through 3-D image data provided by sensors like ToF (Time-of-Flight)

Cited by 88 publications

References 6 publications

Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors

Neural Network Based Data Fusion for Hand Pose Recognition with Multiple ToF Sensors

Real-Time Range Imaging in Health Care: A Survey

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

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