Image Scene Recognition

Abstract

Systems, methods, and computer program products may be directed to creating an image hash. Key points can be identified at different locations within a sample image. Descriptor vectors for the key points can be identified, the descriptor vectors describing local image information around the key points, where each descriptor vector is an n-dimensional array. Key points can be generated based on hashes of data vectors that include at least one of the descriptors, where each feature is a 36×20 hash value.

What is claimed is: 
     
         1 . A method of creating an image hash, comprising:
 identifying features at different locations within a sample image;   identifying descriptor vectors for at least a subset of the features, the subset defining key points of the image, the descriptor vectors describing local image information around the key points, where each descriptor vector is an n-dimensional array and is represented as a unary feature of dimension 128×128; and   generating key points based on hashes of data vectors that include at least one of the descriptors, where each feature is a 36×20 hash value.   
     
     
         2 . The method of  claim 1 , wherein the hashes are performed using a hash function for which a probability that the hash of an arbitrary first vector corresponds to the hash of an arbitrary second vector is a function of a range between the first vector and the second vector. 
     
     
         3 . The method of  claim 2 , wherein the hash function generates a characteristic data string from a data vector larger than the characteristic data string, wherein the arbitrary first vector is a first descriptor vector, and the arbitrary second vector is a second descriptor vector. 
     
     
         4 . The method of  claim 2 , wherein each feature corresponds to multiple keypoints, and each feature is a 36×20 has value. 
     
     
         5 . The method of  claim 1 , wherein each feature comprises:
 a hash value of a first descriptor vector for a first keypoint,   a hash value of a second descriptor vector for a second key point,   a first quantization function mapping an orientation of the first key point in relation to the second key point to a range of integers, and   a second quantization function mapping an orientation of the second key point in relation to the first key point to the range of integers.   
     
     
         6 . The method of  claim 1 , further comprising executing a quantization function mapping an orientation of each key point to a range of integers. 
     
     
         7 . The method of  claim 1 , wherein each hash value is calculated by using a fast algorithm in combination with a sift algorithm. 
     
     
         8 . The method of  claim 1 , wherein each key point is obtained using a fast algorithm. 
     
     
         9 . The method of  claim 1 , wherein each descriptor vector is obtained using a sift algorithm.