Sketch recognition

About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.

Early Recognition and Prediction of Gestures

Abstract: This paper is concerned with an early recognition and prediction algorithm of gestures. Early recognition is the algorithm to provide recognition results before input gestures are completed. Motion prediction is the algorithm to predict the subsequent posture of the performer by using early recognition. In addition to them, this paper considers a gesture network for improving the performance of these algorithms. The performance of the proposed algorithm was evaluated by experiments of real-time control of a humanoid by gestures.

Digital Clay: Deriving Digital Models from Freehand Sketches

Abstract: During the initial stages of design, it is not uncommon to find an architect scribbling furiously with a thick pencil. Later in the design process, however, one might not be surprised to encounter the same individual in front of a computer monitor, manipulating three dimensional models in a series of activities that seem completely divorced from their previous efforts. Armed with evidence that sketching is an effective design method for creative individuals, we also recognize that modeling and rendering applications are invaluable design development and presentation tools, and we naturally seek a connection between these methodologies. We therefore present Digital Clay, a working prototype of a sketch recognition program that interprets gestural and abstracted projection drawings and constructs appropriate three dimensional digital models.

Face Sketch Synthesis via Sparse Representation

Abstract: Face sketch synthesis with a photo is challenging due to that the psychological mechanism of sketch generation is difficult to be expressed precisely by rules. Current learning-based sketch synthesis methods concentrate on learning the rules by optimizing cost functions with low-level image features. In this paper, a new face sketch synthesis method is presented, which is inspired by recent advances in sparse signal representation and neuroscience that human brain probably perceives images using high-level features which are sparse. Sparse representations are desired in sketch synthesis due to that sparseness can adaptively selects the most relevant samples which give best representations of the input photo. We assume that the face photo patch and its corresponding sketch patch follow the same sparse representation. In the feature extraction, we select succinct high-level features by using the sparse coding technique, and in the sketch synthesis process each sketch patch is synthesized with respect to high-level features by solving an $l_1$-norm optimization. Experiments have been given on CUHK database to show that our method can resemble the true sketch fairly well.

Gesture recognition using the XWand

Abstract: The XWand is a wireless UI device that enables styles of natural interaction with intelligent environments. The XWand system exploits human intuition, allowing control of everyday objects through pointing and gesturing. We describe the hardware device and then examine several approaches to gesture recognition. We discuss results from experiments using a linear time warping method, a dynamic time warping (DTW) method, and a hidden Markov modelbased method (HMM).